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iabetes mellitus is a disease that increases the risk of human mortality, particularly that due to coronary heart disease (1). Less-severe forms of impaired carbohydrate metabolism (ICM) are not only the best predictors of future incidence of diabetes (2-5) but also have been postuHAROLD W. KOHL, MSPH JESUS A. VILLEGAS, MD STEVEN N. BLAIR, PED lated as conditions that may increase NEIL F. GORDON, MBBCH, PHD, MPH the risk for death due to all causes and to cardiovascular disease in particular. However, studies on this issue have provided conflicting evidence (6— OBJECTIVE — To determine the association of baseline cardiorespiratory fitness 10). to all-cause mortality across the range of blood glucose levels. Higher levels of physical activity and cardiorespiratory fitness, on the RESEARCH DESIGN AND METHODS— Data from a prospective study of other hand, are believed to reduce the 8715 men (average age 42 yr), followed for an average of 8.2 yr (range 1-15 yr), risk of death due to all causes, cardio were analyzed. Cardiorespiratory fitness was assessed by maximal-exercise treadvascular disease, and perhaps some mill testing. Men with evidence of clinical vascular disease or who did not achieve cancers (11-14). Furthermore, data 85% of their age-predicted maximum heart rate during exercise testing were from both animals (15,16) and humans excluded from analyses. (17-20) show that higher levels of exRESULTS— Age-adjusted death rates increased with higher levels of fasting ercise and fitness may favorably affect blood glucose. Regardless of glycemic status, fit men had lower age-adjusted glucose homeostasis. Thus, high levels all-cause death rates than their less fit counterparts. For men with fasting blood of physical activity and fitness might be glucose >7.8 mM or physician-diagnosed non-insulin-dependent diabetes mellitus beneficial in improving the mortality (NIDDM), the age-adjusted death rates per 10,000 person-yr of follow-up in unfit experience of people with ICM. Aland fit subjects were 82.5 and 45.9, respectively. The age-adjusted relative risk of though this rationale provides the basis death due to all causes was significantly elevated in the lower-fitness group within for exercise and increased physical fiteach of three glycemic status levels: fasting blood glucose 7.8 mellitus, long-term effects of exercise mM or with NIDDM, RR=1.80 (95% CI 1.25-2.58). Multivariate analyses, and fitness in these patients are virtucontrolling for risk factors of mortality (age, resting systolic blood pressure, serum ally unknown. It is partly for this reacholesterol, body mass index, family history of heart disease, follow-up interval, son that, after critically evaluating the and smoking habit) showed a higher risk of death due to all causes for unfit results of available studies, a recent Nacompared with fit men. Multivariate risks of death associated with low fitness, tional Institutes of Health Consensus compared with higher fitness (RR), in the three glycemic status groups were: Development Conference (21) exfasting blood glucose 7.8 mM or with NIDDM, RR = 1.92 (95% CI 0.75-4.90). mellitus (NIDDM). CONCLUSIONS— These data suggest that risk of death increases with lessIt is possible that regular physifavorable glycemic status, and that cardiorespiratory fitness may attenuate the cal activity might benefit patients with forces of impaired carbohydrate metabolism on mortality from any cause. ICM even if glycemic control is not improved, but no data are available on this issue. The purpose of this study is FROM THE DIVISIONS OF EPIDEMIOLOGY AND EXERCISE PHYSIOLOGY, INSTITUTE FOR AEROBICS REto report the results of an investigation SEARCH, DALLAS, TEXAS. into the association of baseline cardioADDRESS CORRESPONDENCE AND REPRINT REQUESTS TO H.W. KOHL, MSPH, DIVISION OF EPIDEMIOLrespiratory fitness to subsequent allOGY, INSTITUTE FOR AEROBICS RESEARCH, 12330 PRESTON ROAD, DALLAS, TX 75230. cause mortality in men across the range RECEIVED FOR PUBLICATION 14 MAY 1991 AND ACCEPTED IN REVISED FORM 6 SEPTEMBER 1991. of glycemic control.
Cardiorespiratory Fitness, Glycemic Status, and Mortality Risk in Men
184
DIABETES CARE, VOLUME 15, NUMBER 2, FEBRUARY 1992
Kohl and Associates
those who did not reach at least 85% of within the three glycemic groups and RESEARCH DESIGN AND METHODS— Subjects in this study their age-predicted maximal heart rate were age-adjusted by the direct method were 8715 male patients (age 20-84 (220-age) were excluded from further with the total follow-up in each cateyr) of a preventive medicine clinic in study. Total duration of this test is gory as the standard. Multivariate estiDallas, Texas, who were examined at highly correlated with measured O 2 up- mation of relative risks (RR) with logisbaseline between 1971 and 1982; 190 take in healthy men (26). tic regression was used to examine the Quintile cutoff points were de- independent effects of cardiorespiratory (age 21-79 yr) subsequently died. All subjects were free of exercise and rest- fined from the population age-group- fitness as a risk factor for all-cause ing electrocardiographically determined specific distribution of treadmill times. mortality in each glycemic control coronary heart disease, self-reported Physically unfit men (n = 1365) were group after adjustment for potential history of myocardial infarction, stroke, denned as those in the bottom 20% of confounding variables of mortality. or hypertension at baseline. Further- the treadmill time distribution; all othmore, patients who reported being ers were categorized as fit (n = 7350). treated with insulin were also excluded. Previous work from our group has RESULTS— The data in Table 1 are A complete preventive medical identified individuals in the 1st quintile baseline descriptive information and examination was given to all subjects as being at significantly increased risk risk-factor status of each of the three after an overnight fast. Medical history of death, relative to more-fit people glycemic groups. Means and 95% confidence intervals (CD for continuous and demographic information, health (13). Glycemic status was defined data and percentage distributions of habits, anthropometry, blood chemistry analysis, blood pressures, electrocardio- from values measured from fasting smoking status are presented. Variables graphy, and a cardiorespiratory fitness blood glucose and self-report of physi- in Table 1 generally show an unfavordetermination by maximal-exercise cian-diagnosed diabetes mellitus. Glu- able trend across the three groupings. treadmill testing were included as part cose tolerance tests were not available Specifically, mean age, weight, body of the examination. Serum glucose in for these patients. Three levels of blood mass index (BMI), blood pressure, and these subjects was measured after a glucose profile were created concordant cholesterol are higher in men with 12-h overnight fast. Specifically, serum with the recommendations of the Na- higher levels of fasting blood glucose. glucose was measured with the hexoki- tional Diabetes Data Group (27): group Mean time on treadmill (cardiorespinase-glucose- 6 - phosphate dehydroge- 1, fasting blood glucose 7.8 mM or a reported personal hisAll-cause mortality rates by glyported previously (13,22-23). There are several distinct dimen- tory of NIDDM. All cases of insulin- cemic status within each of the two sions to physical fitness (24), but we dependent diabetes mellitus were ex- fitness groupings are shown in Fig. 1. refer to cardiorespiratory fitness (mea- cluded from these analyses. The Fit men with fasting blood glucose sured by time on maximal-exercise number of men in each of the three 8 yr, and linear trend of increasing death rates maximal-exercise treadmill test (25). the total follow-up experience in this across glycemic status groups was seen Treadmill speed was begun at 88 cohort was 64,784 person-yr. Mortality in the fit men (slope = 18.2, 95% m/min. A 0% grade was maintained for follow-up used various sources to CI = 3.3-33.1). The unfit men also the 1st min of the test. The grade was achieve a 94% vital status ascertainment demonstrated an increasing slope (2.8), increased to 2% the 2nd min of the test rate. Official death certificates were ob- but CIs around this estimate included and was subsequently raised 1% each tained for most (88%) decedents, and unity (—15.2-20.7). Moreover, within minute of the test up to the 25th min. causes of death were coded by a nosol- each class of glycemic status, those who After this time, the speed of the tread- ogist with the International Classification were fit had lower mortality rates than those who were unfit. Note that those mill was increased 5.4 m/min until test of Diseases, 9th revision (ICD-9). termination. Patients were encouraged Mortality rates were computed men who were fit and were in the most to give maximal effort on the test and for each of the two fitness categories unfavorable glycemic control category
DIABETES CARE, VOLUME 15,
NUMBER 2,
FEBRUARY
1992
185
Fitness, glycemic status, and mortality risk
Table 1—Descriptive information and risk-factor status by glycemic status (Cooper Clinic healthy men, 1971-1985)
>7.8 MM OR NIDDM 3 yr) (13). Although this Fasting Blood Glucose (mmol/l) does not definitively rule out the presence of subclinical disease, it would inFigure 2—Age-adjusted cardiovascular disease death rates/10,000 person-yr oj observation by dicate that such an effect is not biasing fitness grouping within glycemic status (Cooper Clinic men, 1971-1985). Numbers oj deaths on the mortality results. which each rate is based are in parentheses above bars. Our study population was largely from middle to upper socioeconomic classes and was generally welleducated, who chose to come to a prejusted rates is through beneficial effects such misclassification is possible, our ventive medicine clinic for an elective on these or other factors that may not investigation of the mortality experience medical evaluation. However, the study have been completely controlled for or across the range of fasting plasma glu- group was similar on key physiological were not available for analysis in this cose levels would seem to minimize the variables when compared with other study (i.e., insulin sensitivity, adiposity problem, especially given the trends of representative samples of North-Amerior fat distribution, platelet aggregability, increasing death rates across glycemic can men (29). Blood pressures, estimates of maximal O 2 uptake, and body coronary perfusion, and propensity categories. toward ventricular arrhythmias). PhysiInstability in some death rates in weight were similar to those of men in cally fit people may also have larger, these analyses is an issue. There was a the Lipid Research Clinics Prevalence more muscular hearts and could, there- total of four deaths (2 due to cardiovas- Study and the Canada Fitness Survey. fore, be more likely to survive acute cular disease) in the unfit men whose Moreover, total cholesterol was actually myocardial infarctions. fasting glucose values were 2:7.8 raM slightly higher, on the average, in our There are several possible limita- or who had NIDDM. This may help subjects than in the Lipid Research tions to our study, one of which is the explain why the death rates (all cause Clinics data, and the prevalence of ICM method of classifying these men into and cardiovascular disease) were greater was similar to that estimated for all exposure groups. The National Diabetes in low-fitness men with fasting glucose U.S. men (30). Data Group recommends two fasting values 6.4-7.8 mM compared with the Although physical activity was plasma glucose determinations and ^7.8 mM or NIDDM category. The in- not directly analyzed in these analyses, sometimes an oral glucose tolerance test stability is further evidenced by the it is possible to estimate the amount of to correctly diagnose individuals as wide CIs around the risk estimates in exercise necessary to move from the having diabetes mellitus or impaired this group (Table 3). The choice to low-fitness group (lower 20%) to the glucose tolerance (27). Our measure of maintain the clinically relevant catego- higher-fitness group. For example, the glycemic status was a single fasting ries for analyses was more important estimated maximal O 2 uptake for a 40plasma glucose value. Thus, the pres- than having equivalent representation to 49-yr-old man in this study who ence of false-positives and false-nega- among groupings. was in the lower 20% of the fitness 1 tives cannot be ruled out. Although The maximal heart rate and dis- distribution would be
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iabetes mellitus is a disease that increases the risk of human mortality, particularly that due to coronary heart disease (1). Less-severe forms of impaired carbohydrate metabolism (ICM) are not only the best predictors of future incidence of diabetes (2-5) but also have been postuHAROLD W. KOHL, MSPH JESUS A. VILLEGAS, MD STEVEN N. BLAIR, PED lated as conditions that may increase NEIL F. GORDON, MBBCH, PHD, MPH the risk for death due to all causes and to cardiovascular disease in particular. However, studies on this issue have provided conflicting evidence (6— OBJECTIVE — To determine the association of baseline cardiorespiratory fitness 10). to all-cause mortality across the range of blood glucose levels. Higher levels of physical activity and cardiorespiratory fitness, on the RESEARCH DESIGN AND METHODS— Data from a prospective study of other hand, are believed to reduce the 8715 men (average age 42 yr), followed for an average of 8.2 yr (range 1-15 yr), risk of death due to all causes, cardio were analyzed. Cardiorespiratory fitness was assessed by maximal-exercise treadvascular disease, and perhaps some mill testing. Men with evidence of clinical vascular disease or who did not achieve cancers (11-14). Furthermore, data 85% of their age-predicted maximum heart rate during exercise testing were from both animals (15,16) and humans excluded from analyses. (17-20) show that higher levels of exRESULTS— Age-adjusted death rates increased with higher levels of fasting ercise and fitness may favorably affect blood glucose. Regardless of glycemic status, fit men had lower age-adjusted glucose homeostasis. Thus, high levels all-cause death rates than their less fit counterparts. For men with fasting blood of physical activity and fitness might be glucose >7.8 mM or physician-diagnosed non-insulin-dependent diabetes mellitus beneficial in improving the mortality (NIDDM), the age-adjusted death rates per 10,000 person-yr of follow-up in unfit experience of people with ICM. Aland fit subjects were 82.5 and 45.9, respectively. The age-adjusted relative risk of though this rationale provides the basis death due to all causes was significantly elevated in the lower-fitness group within for exercise and increased physical fiteach of three glycemic status levels: fasting blood glucose 7.8 mellitus, long-term effects of exercise mM or with NIDDM, RR=1.80 (95% CI 1.25-2.58). Multivariate analyses, and fitness in these patients are virtucontrolling for risk factors of mortality (age, resting systolic blood pressure, serum ally unknown. It is partly for this reacholesterol, body mass index, family history of heart disease, follow-up interval, son that, after critically evaluating the and smoking habit) showed a higher risk of death due to all causes for unfit results of available studies, a recent Nacompared with fit men. Multivariate risks of death associated with low fitness, tional Institutes of Health Consensus compared with higher fitness (RR), in the three glycemic status groups were: Development Conference (21) exfasting blood glucose 7.8 mM or with NIDDM, RR = 1.92 (95% CI 0.75-4.90). mellitus (NIDDM). CONCLUSIONS— These data suggest that risk of death increases with lessIt is possible that regular physifavorable glycemic status, and that cardiorespiratory fitness may attenuate the cal activity might benefit patients with forces of impaired carbohydrate metabolism on mortality from any cause. ICM even if glycemic control is not improved, but no data are available on this issue. The purpose of this study is FROM THE DIVISIONS OF EPIDEMIOLOGY AND EXERCISE PHYSIOLOGY, INSTITUTE FOR AEROBICS REto report the results of an investigation SEARCH, DALLAS, TEXAS. into the association of baseline cardioADDRESS CORRESPONDENCE AND REPRINT REQUESTS TO H.W. KOHL, MSPH, DIVISION OF EPIDEMIOLrespiratory fitness to subsequent allOGY, INSTITUTE FOR AEROBICS RESEARCH, 12330 PRESTON ROAD, DALLAS, TX 75230. cause mortality in men across the range RECEIVED FOR PUBLICATION 14 MAY 1991 AND ACCEPTED IN REVISED FORM 6 SEPTEMBER 1991. of glycemic control.
Cardiorespiratory Fitness, Glycemic Status, and Mortality Risk in Men
184
DIABETES CARE, VOLUME 15, NUMBER 2, FEBRUARY 1992
Kohl and Associates
those who did not reach at least 85% of within the three glycemic groups and RESEARCH DESIGN AND METHODS— Subjects in this study their age-predicted maximal heart rate were age-adjusted by the direct method were 8715 male patients (age 20-84 (220-age) were excluded from further with the total follow-up in each cateyr) of a preventive medicine clinic in study. Total duration of this test is gory as the standard. Multivariate estiDallas, Texas, who were examined at highly correlated with measured O 2 up- mation of relative risks (RR) with logisbaseline between 1971 and 1982; 190 take in healthy men (26). tic regression was used to examine the Quintile cutoff points were de- independent effects of cardiorespiratory (age 21-79 yr) subsequently died. All subjects were free of exercise and rest- fined from the population age-group- fitness as a risk factor for all-cause ing electrocardiographically determined specific distribution of treadmill times. mortality in each glycemic control coronary heart disease, self-reported Physically unfit men (n = 1365) were group after adjustment for potential history of myocardial infarction, stroke, denned as those in the bottom 20% of confounding variables of mortality. or hypertension at baseline. Further- the treadmill time distribution; all othmore, patients who reported being ers were categorized as fit (n = 7350). treated with insulin were also excluded. Previous work from our group has RESULTS— The data in Table 1 are A complete preventive medical identified individuals in the 1st quintile baseline descriptive information and examination was given to all subjects as being at significantly increased risk risk-factor status of each of the three after an overnight fast. Medical history of death, relative to more-fit people glycemic groups. Means and 95% confidence intervals (CD for continuous and demographic information, health (13). Glycemic status was defined data and percentage distributions of habits, anthropometry, blood chemistry analysis, blood pressures, electrocardio- from values measured from fasting smoking status are presented. Variables graphy, and a cardiorespiratory fitness blood glucose and self-report of physi- in Table 1 generally show an unfavordetermination by maximal-exercise cian-diagnosed diabetes mellitus. Glu- able trend across the three groupings. treadmill testing were included as part cose tolerance tests were not available Specifically, mean age, weight, body of the examination. Serum glucose in for these patients. Three levels of blood mass index (BMI), blood pressure, and these subjects was measured after a glucose profile were created concordant cholesterol are higher in men with 12-h overnight fast. Specifically, serum with the recommendations of the Na- higher levels of fasting blood glucose. glucose was measured with the hexoki- tional Diabetes Data Group (27): group Mean time on treadmill (cardiorespinase-glucose- 6 - phosphate dehydroge- 1, fasting blood glucose 7.8 mM or a reported personal hisAll-cause mortality rates by glyported previously (13,22-23). There are several distinct dimen- tory of NIDDM. All cases of insulin- cemic status within each of the two sions to physical fitness (24), but we dependent diabetes mellitus were ex- fitness groupings are shown in Fig. 1. refer to cardiorespiratory fitness (mea- cluded from these analyses. The Fit men with fasting blood glucose sured by time on maximal-exercise number of men in each of the three 8 yr, and linear trend of increasing death rates maximal-exercise treadmill test (25). the total follow-up experience in this across glycemic status groups was seen Treadmill speed was begun at 88 cohort was 64,784 person-yr. Mortality in the fit men (slope = 18.2, 95% m/min. A 0% grade was maintained for follow-up used various sources to CI = 3.3-33.1). The unfit men also the 1st min of the test. The grade was achieve a 94% vital status ascertainment demonstrated an increasing slope (2.8), increased to 2% the 2nd min of the test rate. Official death certificates were ob- but CIs around this estimate included and was subsequently raised 1% each tained for most (88%) decedents, and unity (—15.2-20.7). Moreover, within minute of the test up to the 25th min. causes of death were coded by a nosol- each class of glycemic status, those who After this time, the speed of the tread- ogist with the International Classification were fit had lower mortality rates than those who were unfit. Note that those mill was increased 5.4 m/min until test of Diseases, 9th revision (ICD-9). termination. Patients were encouraged Mortality rates were computed men who were fit and were in the most to give maximal effort on the test and for each of the two fitness categories unfavorable glycemic control category
DIABETES CARE, VOLUME 15,
NUMBER 2,
FEBRUARY
1992
185
Fitness, glycemic status, and mortality risk
Table 1—Descriptive information and risk-factor status by glycemic status (Cooper Clinic healthy men, 1971-1985)
>7.8 MM OR NIDDM 3 yr) (13). Although this Fasting Blood Glucose (mmol/l) does not definitively rule out the presence of subclinical disease, it would inFigure 2—Age-adjusted cardiovascular disease death rates/10,000 person-yr oj observation by dicate that such an effect is not biasing fitness grouping within glycemic status (Cooper Clinic men, 1971-1985). Numbers oj deaths on the mortality results. which each rate is based are in parentheses above bars. Our study population was largely from middle to upper socioeconomic classes and was generally welleducated, who chose to come to a prejusted rates is through beneficial effects such misclassification is possible, our ventive medicine clinic for an elective on these or other factors that may not investigation of the mortality experience medical evaluation. However, the study have been completely controlled for or across the range of fasting plasma glu- group was similar on key physiological were not available for analysis in this cose levels would seem to minimize the variables when compared with other study (i.e., insulin sensitivity, adiposity problem, especially given the trends of representative samples of North-Amerior fat distribution, platelet aggregability, increasing death rates across glycemic can men (29). Blood pressures, estimates of maximal O 2 uptake, and body coronary perfusion, and propensity categories. toward ventricular arrhythmias). PhysiInstability in some death rates in weight were similar to those of men in cally fit people may also have larger, these analyses is an issue. There was a the Lipid Research Clinics Prevalence more muscular hearts and could, there- total of four deaths (2 due to cardiovas- Study and the Canada Fitness Survey. fore, be more likely to survive acute cular disease) in the unfit men whose Moreover, total cholesterol was actually myocardial infarctions. fasting glucose values were 2:7.8 raM slightly higher, on the average, in our There are several possible limita- or who had NIDDM. This may help subjects than in the Lipid Research tions to our study, one of which is the explain why the death rates (all cause Clinics data, and the prevalence of ICM method of classifying these men into and cardiovascular disease) were greater was similar to that estimated for all exposure groups. The National Diabetes in low-fitness men with fasting glucose U.S. men (30). Data Group recommends two fasting values 6.4-7.8 mM compared with the Although physical activity was plasma glucose determinations and ^7.8 mM or NIDDM category. The in- not directly analyzed in these analyses, sometimes an oral glucose tolerance test stability is further evidenced by the it is possible to estimate the amount of to correctly diagnose individuals as wide CIs around the risk estimates in exercise necessary to move from the having diabetes mellitus or impaired this group (Table 3). The choice to low-fitness group (lower 20%) to the glucose tolerance (27). Our measure of maintain the clinically relevant catego- higher-fitness group. For example, the glycemic status was a single fasting ries for analyses was more important estimated maximal O 2 uptake for a 40plasma glucose value. Thus, the pres- than having equivalent representation to 49-yr-old man in this study who ence of false-positives and false-nega- among groupings. was in the lower 20% of the fitness 1 tives cannot be ruled out. Although The maximal heart rate and dis- distribution would be
