Serum lipoprotein(a) [Lp(a)] levels were measured before and after a 12-wk program of moderate-intensity endurance training. The training program consisted of walking and/or jogging, at least three sessions·wk-1 of at least 30 min duration, at an intensity producing 60-85% HRmax reserve. Twenty-eight previously sedentary middle-aged Caucasian males matched for age, body mass, and body mass index(BMI) were randomly allocated to either an exercise (N = 17, mean age ± SEM = 51.57 ± 1.25 yr) or a control (N = 11, mean age ± SEM = 50.0 ± 1.15 yr) group. Pre- and post-training median Lp(a) levels, measured by immunoturbidimetric analysis, were not significantly different in either the exercise (pre 13.0, post 15.0 mg·dl-1) or the control subjects (pre 14.0, post 12.0 mg·dl-1)(P > 0.05). Kendall Rank correlation analysis revealed no significant relationship between the level of Lp(a) and any other variable in either group before or after training. In the exercisers, a significant increase (P < 0.05) was recorded in the estimated mean ˙VO2max (pre 33.39 ± 1.70, post 37.7 ± 1.75 ml·kg-1·min-1). These data indicate that the level of Lp(a) was not influenced by a 12-wk program of moderate-intensity endurance training, and are consistent with previous reports suggesting that Lp(a) level is not altered by lifestyle factors.
Department of Human Movement Studies, The University of Queensland, Queensland 4072, AUSTRALIA
Submitted for publication June 1995.
Accepted for publication January 1996.
The authors acknowledge the advice and assistance given by Dr. Alf Howard in the statistical analysis of the study; and Dr. Charlie Appleton, Pathologist, and Mark Blakey, Biochemist, Queensland Medical Laboratory, West End, Brisbane, for assistance in the measurement of lipoproteins.
Address for correspondence: Dr. Laurel Traeger Mackinnon, Department of Human Movement Studies, The University of Queensland, Queensland 4072, Australia. E-mail: email@example.com.
Lipoprotein(a) [Lp(a)] has a lipid component very similar to that of the low density lipoprotein (LDL). The protein component is formed by two distinct proteins [apolipoprotein B-100 and apolipoprotein(a)], linked by a disulfide bond to form a macromolecule (2). Lp(a) is characterized by the presence of apolipoprotein(a), a glycoprotein that has a strong similarity to plasminogen (48). First discovered by Berg in 1963, (8) Lp(a) appears to have a role in the atherosclerotic process either by inducing cholesterol deposits in the arterial wall and/or interfering with coagulation(31,32). For example, elevated Lp(a) levels have been associated with increased risk for atherosclerotic coronary heart disease(CHD), for cerebrovascular disease, and in restenosis of coronary bypass grafts (5,15,23,30,38). Moreover, when Lp(a) levels are greater than 30 mg·dl-1 and LDL levels are also elevated, the risk for atherosclerosis appears to escalate quite markedly (10). The level of Lp(a) is an inherited genetic trait (8) and in Caucasians, the distribution is skewed toward low levels (44,48).
Regular moderate endurance exercise appears to have a major role, both directly and indirectly, by favorably modifying lipoprotein subfractions, and thereby reducing some of the risk for CHD (reviews,9,20). Unlike other lipoproteins, the level of Lp(a) is mostly resilient to drug and/or dietary manipulation(1,3), and largely unaffected by age or gender (at least prior to menopause) (39). Of considerable interest, therefore, is the response of Lp(a) to regular moderate endurance training.
Results from the few published cross-sectional and intervention studies on the influence of exercise on Lp(a) have been inconsistent. For example, some preliminary observational investigations have suggested that physical activity may influence the level of Lp(a) (6,12); others have not (24,25,45,46). Some training studies indicate no significant response of Lp(a) to training periods of 6-12 months of moderate-intensity endurance training(33,40). Other studies have reported significant decreases in the Lp(a) level following endurance training(21,22), and a detraining period of 14-22 d has resulted in a significant borderline increase in Lp(a)(34).
Our previous cross-sectional investigation found no relationship between Lp(a) and physical activity in healthy middle-aged distance runners and matched controls. Therefore, it was decided to conduct an intervention study in which issues of the skewness of the Lp(a) distribution, and difficulty with the international standardization of the assay method for Lp(a), are less problematic.
The purpose of this study was to determine whether the level of Lp(a) was altered by a 12-wk moderate-intensity endurance training program in previously sedentary middle-aged males.
Age, height, body mass, and body mass index (BMI) were recorded on a large pool (N = 50) of male Caucasian subjects in the age range 40-60 yr. The subjects were then matched on age, body mass, and BMI, and randomly allocated to either a training or to a control group. Matching first took place on age (born in the same year); once the groups were matched for age, subjects were then matched on body mass (±1.0 kg) and finally on BMI(±0.50 kg·m-2). Data from a physical activity inventory confirmed the sedentary status of all subjects prior to the commencement of the study. Sedentary was defined as no regular exercise, either occupationally or recreationally, for the past 3 yr except for the occasional walk (less than once every 2 wk), game of golf or tennis. Cigarette smoking history indicated that there were no current smokers in either group; two of the exercisers, and one of the control subjects, were ex-smokers but had ceased smoking more than 15 yr before.
Seventeen middle-aged males formed the training group (mean age ± SEM = 51.57 ± 1.25 yr). Eleven middle-aged males (mean age = 50.0± 1.15 yr) acted as control subjects and completed all requirements of the study except for the 12-wk endurance training intervention. One exercising subject withdrew from the original training group of 18 for reasons unrelated to the study.
All subjects participated with written informed consent and completed a medical history, physical activity inventory, food diary, training diary(exercisers), and activity diary (controls). None of the subjects was taking medication known to influence plasma lipoprotein levels, and no subject reported diagnosed coronary heart disease (CHD). The study was approved by The University of Queensland Human Experimentation Ethical Review Committee.
Nine skinfold sites were located (37) and measured to the nearest 0.2 mm using a Holtain skinfold caliper (Holtain Ltd, Crymich, UK). Skinfolds were measured at the same time of day (8:00 to 9:00 a.m.), at three timepoints-before, midway, and after the 12-wk period. The sum of six skinfold sites was calculated and percent body fat was estimated from age- and sex-related tables (36).
Body circumference measures were recorded at the level of the waist, umbilicus, hip, and greater trochanter, enabling the following ratios to be determined: waist/hip, umbilicus/hip, and umbilicus/trochanter as previously described (11).
Food diaries were kept by all subjects. Energy intake was determined using the average of food and beverages consumed on three weekdays at three timepoints (before, midway, and after the 12 wk). Dietary analysis was performed by computer program using an Australian nutrient database (Diet 1, Xyris Software, Brisbane, Australia). During the study all subjects (including controls) were requested to maintain normal diet and body mass over the 12-wk period.
Estimation of Aerobic Capacity
Aerobic capacity of all subjects was estimated before and after training using the modified Sjostrand Bicycle Ergometer Multiple Stage Test(18), which is suitable for older and untrained individuals. During the ergometer test, heart rate and the electrical activity of the heart were monitored via a three-lead exercise electrocardiograph (ECG) using the Reigel Cardiac Monitor.
Exercising subjects were requested to walk and/or jog at low to moderate intensity (60-85% HRmax reserve), 3 d·wk-1 for at least 30 min each session for 12 wk. Heart rate reserve (HRR) is defined as (maximal heart rate - resting heart rate), where maximal heart rate is calculated as 220 - age. The training heart rate is then calculated as a percentage of the HRR + the resting heart rate (HRmax reserve). Subjects were instructed in the palpation method of heart rate monitoring, calculation of training heart rates (27), the walking speed required to elicit the training heart rate, and with the components of the endurance training session (i.e., warm-up, workout, and cool-down). In addition, detailed written instructions were also provided and the training program was partially supervised. The investigator attended at least one, and sometimes two, sessions per week for each exercising subject. Subjects were also telephoned and encouraged to adhere to the program and to maintain their training diary.
Blood samples were obtained from the antecubital vein and were collected between 8:00 and 9:00 a.m. All subjects fasted for 12 h and had not consumed alcohol or exercised for 48 h prior to blood sampling.
Samples were stored at 5°C until assayed within 24 h for lipoproteins and apoproteins, and within 1 wk for Lp(a). Lp(a) samples were assayed weekly, since Lp(a) samples are stable at 4°C for 1 month(35). Lipoprotein(a) was determined using an automated procedure by immunoturbidimetric analysis using the Cobas Fara II centrifugal analyzer (Roche, Basel, Switzerland). A polyclonal IgG antibody (Incastar Corporation, Stillwater, OK) was used. Within- and between-run imprecision was indicated by a coefficient of variation (CV) of less than 10% for all levels tested (6-49 mg·dl-1) for in-house Lp(a) sampling over a 2-yr period. Sensitivity was 6 mg·dl-1, and no interference was shown for plasminogen, apolipoprotein B, or triglycerides. The laboratory was one of seven Australian laboratories participating in an International Lp(a) Standardization Pilot Study conducted by Northwest Lipid Research Laboratories in the U.S. The in-house precision for the immunoturbidimetric method demonstrated a high correlation (r = 0.98) and a low CV% (9.3) with assigned values from an external laboratory during the pilot study (unpublished data). None of the subjects had Lp(a) levels outside the range of the Incastar Lp(a) kit (i.e., between 6 and 100 mg·dl-1). It was not feasible to carry out Lp(a) phenotyping in this study.
Total cholesterol (4) and triglyceride(17,47) were determined by automated enzymatic methods (Technicon Instruments Corporation, Tarrytown, NY). High and low density lipoprotein cholesterol were determined using the Rep HDL-30 Electrophoresis System (Helena Laboratories, Beaumont, TX)(13). Quantification of Apo A-I and B were measured separately by rate nephelometry using a Behring automated nephelometer (Werke AG Diagnostica, Marburg, Germany).
Coefficients of skewness and kurtosis were calculated to test deviations from normality for all variables. Logarithmic transformation was performed on the individual values of the skewed variables before statistical computations and significance testing. Mean and median values were calculated for all variables. Training study data that were normally distributed were analyzed using two-way (time × group) analysis of variance (ANOVA) with time as a repeated measure. For data that were not normally distributed, a Kruskal-Wallis ANOVA was used to examine between-group comparisons and a Friedman ANOVA to determine changes over time.
Correlational analysis was performed to determine whether Lp(a) levels were statistically related to other variables. Kendall Rank Correlation analysis was used on non-parametric data with the Bonferroni correction factor applied(28).
Multiple regression analysis was performed on all variables to account for the percent contribution of the variance in Lp(a) by a selected variable. The multiple regression analysis (Regran) used a modification of the program described by Veldman (49). Since the interest was ina priori determined variables in accounting for the variance in Lp(a) levels rather than an overall pattern, no Bonferroni correction was used. For all tests an alpha of 0.05 was accepted as showing statistical significance. When appropriate, post-hoc tests were applied to detect the source of the differences.
Pre-training physical profiles of the exercisers and control subjects are shown in Table 1. For exercisers, training diaries confirmed the frequency (mean ± SEM sessions a week, 4.05 ± 0.17) and duration (mean ± SEM minutes walked, 43.03 ± 3.24) of the weekly sessions. Mean ± SEM training heart rates of the exercisers were 129.47 ± 4.12 bpm (range 118-140 bpm), indicating an intensity for the training program of approximately 72% HRmax reserve (range 60-78% HRmax reserve). Activity diaries kept by control subjects confirmed that their activity levels were unchanged during the 12-wk period. The“dropout” rate (5%) during the training program was lower than rates of 15-20% quoted for programs of this type(16).
The frequency distribution of Lp(a) was highly skewed based on the raw scores and log-transformed values so both mean and median values are reported. Pre-training lipoprotein profiles of the groups were similar(Table 2). Pre- to post-training values for lipoproteins for the exercisers are shown in Table 3. There were no significant differences pre-to post-training in median Lp(a) levels in the exercisers (Table 3). In the control subjects, median Lp(a) levels were not significantly different across the study period (pre 14.0 compared with post 12.0 mg·dl-1). Median Lp(a) levels were not significantly different between exercisers and control subjects before or after training. Following training, TC levels decreased significantly in the exercisers (Table 3). Other lipoproteins were not significantly changed across the 12-wk period in the exercisers(Table 3) or in the control group. The index of risk for heart disease was derived using data from the medical history and health inventory and scored as: 0 for no family history of heart disease, 1 for a cardiac event in either parent >60 yr, and 2 for a cardiac event in either parent <60 yr. The index of risk was not significantly different between the groups (Table 2).
Changes in Other Variables
The changes in the physiological, anthropometric, and body composition variables in the exercisers are shown in Table 4. There was a significant increase in aerobic capacity in the training group(Table 4). Exercisers showed significant decreases(P < 0.01) pre- to post-training in individual skinfold sites[suprailiac (7.7%), abdomen (12%), and thigh (8.8%)], as well as the skinfold sum (7.5%), and estimated body fat% (4.3%), and in the umbilicus and trochanter circumference measures (Table 4). There was a small but significant (P < 0.05) gain pre- to post-training in mean body mass in the control subjects (pre 84.15 ± 1.28 compared with post 84.71 ± 1.17). Pre-training aerobic capacity and body composition variables were unchanged in the control subjects.
There were no significant differences in the dietary variables based on times (pre-, mid- or post-) or conditions (exercisers or controls). Dietary records showed total kcal·wk-1 to be 1756.58 ± 93.49 and 1661.49 ± 89.03 for exercisers and controls, respectively. The composition of the diet for the exercisers and controls was similar: exercisers, saturated fat 27.66 ± 1.77%, carbohydrate 47.09 ± 2.25, and protein 18.20 ± 0.87%; controls, saturated fat 25.32 ± 2.06%, carbohydrate 48.96 ± 2.26%, and protein 17.52 ± 2.06%.
Correlations between Lp(a) and Other Variables
Using Kendall Rank correlation analysis, there was no relationship between the Lp(a) concentration and any lipid, physiological, anthropometric, or dietary variable pre- or post-training in the exercisers or in the control subjects. There was no correlation between Lp(a) and smoking history in either group.
In the exercisers, based on multiple regression analysis, percent body fat accounted for 30% of the variance in the level of Lp(a), [F (1,15) = 6.48, P < 0.05)] (Table 5). However, inclusion in the model of the next variable (Apo B/A-I) from the hierarchical output did not have any further significant effect on the F-ratio value (Table 5). In the control group, percent body fat accounted for 17% of the variance in the level of Lp(a), but the calculatedF-ratio did not reach significance (Table 5).
In the present study, Lp(a) levels did not change in response to a 12-wk program of moderate-intensity endurance training, which improved estimated˙VO2max in previously sedentary, healthy middle-aged males. It is not unexpected that Lp(a) levels did not change after endurance training, as Lp(a) levels are considered to be largely genetically determined(48), and are mostly insensitive to other lifestyle factors such as dietary/drug therapy (2).
The present results support the findings from our previous cross-sectional study, which found no relationship between Lp(a) levels and physical activity in middle-aged male marathon runners (mean weekly training distance ± SEM = 60.72 ± 2.76 km·wk-1) and matched sedentary controls (24). However, results of the few previous studies on exercise and Lp(a) using cross-sectional and intervention study designs are inconsistent. A possible link between physical activity and mean Lp(a) levels in adolescent patients with IDDM has been reported(6), whereas other observational investigations report no significant relationship between Lp(a) and physical fitness in adult men and women (25) or in adolescent boys and girls(46). One study reported higher Lp(a) levels in distance runners than in body builders and sedentary controls(12), whereas another report investigating similar groups did not show this relationship (45).
The present data are in agreement with reports showing that the Lp(a) level was not affected by programs of moderate intensity (60-85% MHR) endurance training such as a 6-month moderate-intensity treadmill walking and cycling training program by postmenopausal women (33); or by 9-12 months of endurance training involving three to five 45-min-to-1-h sessions weekly of walking/jogging or cycle ergometry by normolipidemic men and women (40).
However, other exercise intervention studies have reported changes in the Lp(a) level. Significant decreases in Lp(a) have been recorded following eight consecutive days of cross-country skiing (10 h·d-1)(21), and following 4 wk of moderate swim training in combination with a fish oil supplement in male angina patients(22).
Two of the reports suggesting an influence of exercise on Lp(a) levels may have been confounded by several factors (21,22). For example, the combination of extreme environmental conditions, very heavy exercise, and dietary manipulation during eight consecutive days of cross-country skiing (21) is likely to have contributed to changes in Lp(a). In addition, the significant decrease in the Lp(a) level following a 4-wk moderate-intensity swim training program(22) may have been due to the combination of exercise and fish oil supplementation rather than exercise per se, since decreases in Lp(a) following fish oil supplementation have been previously shown (7). However, dietary modification associated with health-related benefits such as decreasing saturated fat intake do not appear to influence Lp(a) levels (1,3).
Lp(a) levels may only be influenced by very heavy exercise. For example, if the problems of sample size and skewness of Lp(a) are disregarded, it is interesting that in both studies where exercise has been shown to influence Lp(a) levels the exercise treatment has been extreme (i.e., cross-country skiing for eight consecutive days (21) and in runners training 25-30 km daily (12). These findings may suggest that Lp(a) exhibits an acute response to repeated tissue injury resulting from frequent and prolonged movement of large muscle mass(12), whereas tissue damage of this type would not be elicited by a program of moderate-intensity endurance training used in the present investigation by other investigators(33,40). Such programs are routinely prescribed for lifestyle changes involving increasing physical activity levels and thereby promoting health and cardiovascular fitness.
As expected from the literature (1,44), in the present study Lp(a) levels were not normally distributed based on either raw or log-transformed values. The skewness of the Lp(a) distribution raises two issues. First, median rather than mean values should be reported for skewed data (42), and some of the exercise studies have reported means for skewed data (6,21). Second, the estimated sample size that is required when data show a skewed distribution is a major concern. Although this is not such an issue for a within-subject comparison such as the present investigation, sample size must be considered. For example, based on the present results for Lp(a), a power analysis indicated that more than 44 subjects would be required to show significance using procedures suggested by Cohen (14). Since the Friedman ANOVA appears to have an efficiency of 95% (41) these comments should apply equally to non-normally-distributed data. However, sample size becomes problematic for between-subject study designs as indicated in a recent report by the present authors (24). It would appear that all of the exercise/Lp(a) studies mentioned above are impaired by an inadequate sample size, and therefore further work must account for these factors.
In the present study, Kendall Rank Correlation analysis indicated an absence of any significant correlation between the level of Lp(a) and any other variable (lipid, anthropometric, or dietary) in either group pre- or post-training. This result is in agreement with previous reports indicating that Lp(a) levels appear to be independently regulated and unrelated to other lipoprotein levels(2,5,19,29,30). Recent work has also shown no relationship between Lp(a) levels and age, body mass, BMI, alcohol consumption, cigarette smoking, index of risk for heart disease, or other lipoproteins such as TC and LDL-C when corrected for the Lp(a) cholesterol content (26,43). However, it was interesting that, disregarding the lack of normality of Lp(a), multiple regression analysis showed that percent body fat accounted for 30%(P < 0.05), and 17% of the variance in the Lp(a) level(P > 0.05) in the exercisers and controls, respectively. This was not confirmed by Kendall Rank Correlation analysis. Very little can be inferred from this, but this could be an issue of further investigation.
In conclusion, these data indicate that Lp(a) concentrations in previously sedentary middle-aged males were not significantly influenced by a self-monitored 12-wk program of moderate-intensity endurance training consisting of walking and/or jogging at an intensity of 60-85% HRmax reserve. Changes in TC, HDL-C, and Tg were modest. In the exercisers, aerobic capacity was significantly increased, and the sum of skinfolds and percent body fat were significantly decreased following the 12-wk training program. Thus, Lp(a) levels do not appear to change in response to moderate-intensity endurance training despite improvements in aerobic capacity, total cholesterol levels, and body composition. The present data indicate that Lp(a) levels are unaffected by short-term moderate intensity endurance training in previously sedentary middle-aged healthy males, and together with our previous work suggest that physical activity does not alter the Lp(a) level.
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MIDDLE-AGED MALES; APOLIPOPROTEINS; AEROBIC CAPACITY; ENDURANCE
©1996The American College of Sports Medicine