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Physical Activity, Physical Fitness, and Leukocyte Telomere Length

The Cardiovascular Health Study


Author Information
Medicine & Science in Sports & Exercise: December 2015 - Volume 47 - Issue 12 - p 2525-2534
doi: 10.1249/MSS.0000000000000720


Telomere length (TL)—repetitive DNA sequences at the ends of eukaryotic chromosomes that act as “caps,” protecting genomic integrity and stability (46)—has received attention as a potential marker of biologic aging (4,204,20). Leukocyte TL in humans has been associated with age-related diseases, disease biomarkers, and mortality (4,5,9,11,12,30,324,5,9,11,12,30,324,5,9,11,12,30,324,5,9,11,12,30,324,5,9,11,12,30,324,5,9,11,12,30,324,5,9,11,12,30,32). For example, in the Cardiovascular Health Study, shorter TL was associated with higher risk of cardiovascular disease (CVD), age-related disease burden, and mortality (5,11,12,325,11,12,325,11,12,325,11,12,32).

Shortening of TL may be predominantly influenced by oxidative stress and inflammation (33). It has been hypothesized that higher levels of physical activity (PA) and physical fitness (PF) may delay TL shortening, potentially through anti-inflammatory and antioxidative mechanisms (22,4122,41). Greater PA and PF are consistently associated with lower morbidity and mortality from chronic diseases (1), supporting a potential “antiaging” effect. Yet, only limited epidemiologic evidence supports an influence on PA or PF on TL. Among prior studies, some observational studies (7,8,17,18,21,28,34,487,8,17,18,21,28,34,487,8,17,18,21,28,34,487,8,17,18,21,28,34,487,8,17,18,21,28,34,487,8,17,18,21,28,34,487,8,17,18,21,28,34,487,8,17,18,21,28,34,48) and one intervention study (26) suggested favorable roles for PA or PF in TL profiles, but other observational (6,476,47) and intervention (36,4236,42) studies did not. In addition, all of the observational studies assessed only cross-sectional associations of a single PA or PF measure, limiting conclusions on long-term cumulative PA or PF. The two interventional studies were also of short duration (3–6 months), limiting inference on the effects of long-term PA or PF. No prior studies have separately measured PA and PF and assessed whether each of PA and PF was independently associated with TL. For example two of four prior studies had small samples sizes (N < 65), limiting statistical power for detecting associations; none separately evaluated PA and PF to determine their potential independent associations with TL. Finally, few of these prior studies were conducted in older adults (18,28,34,4718,28,34,4718,28,34,4718,28,34,47), a population that is particularly relevant to the study of aging because old age is associated with a high prevalence of chronic diseases and, consequently, a possibly accelerated rate of telomere shortening. A recent 6-month randomized controlled PA trial in 68-yr-old sedentary and overweight subjects suggested that reduced sitting time, but not greater time spent exercising, was associated with telomere lengthening (38). However, this study had a small sample size (N = 49) (38).

To address these issues and to determine whether long-term PA and PF are associated with TL and TL attrition later in life, we investigated the cross-sectional and prospective associations of PA and PF with TL in a community-based cohort study of older US adults.



The design and recruitment process of the Cardiovascular Health Study have been described (13,4413,44). Briefly, 5201 ambulatory noninstitutionalized men and women age 65 yr or older were randomly selected and enrolled from Medicare eligibility lists in four US communities in 1989–1990; an additional 687 Black participants were similarly recruited and enrolled in 1992. The institutional review committee at each center approved the study, and all participants provided a written informed consent form. From 1989–1990 to 1998–1999, participants were followed by annual study visits. Standardized evaluations included physical examination, diagnostic testing, laboratory evaluation, and questionnaires on health status, medical history, and cardiovascular risk factors (13,27,4413,27,4413,27,44). Blood was collected and stored during most visits, and DNA was collected from those participants who provided consent for the use of their genetic material. Individuals from each enrollment phase were included in the present study if they consented to the use of their DNA, had at least 12 mg of DNA available, had stored leukocytes for additional DNA preparation, and had measures of PA and PF at baseline. The characteristics of individuals included in this analysis were generally similar to those of the whole cohort.

Assessment of PA and PF

PA was assessed at multiple serial visits (Figure, Supplemental Digital Content 1, Timeline, Usual leisure-time activity was assessed using a modified validated Minnesota Leisure-Time Activities questionnaire, which has been associated with risk of multiple disease outcomes in this cohort (23). The questionnaire evaluated the frequency and duration of 15 different activities during the prior 2 wk, including gardening, mowing, raking, swimming, hiking, aerobics, tennis, jogging, racquetball, walking, golfing, bicycling, dancing, calisthenics, and exercise cycling (37). Each activity was expressed in metabolic equivalents of task (43), and participant responses to the type, frequency, and duration of each activity were used to calculate weekly energy expenditure (in kilocalories per week) from leisure-time activity. Usual exercise intensity was also assessed (none, low, moderate, high) (37). Usual walking habits, including mean walking pace (gait speed) and distance walked, were assessed annually at each follow-up visit. We evaluated these metrics in prespecified categories, including the following: usual pace walked (<2, 2–3, >3 mph), blocks walked (quintiles), exercise intensity (none, low, moderate, high) and leisure-time activity (quintiles). A previously defined walking score was also evaluated based on the combination of walking pace and walking distance (23).

PF was also assessed at multiple serial visits (Figure, Supplemental Digital Content 1, Timeline assessment of physical activity and physical fitness and telomere length in the Cardiovascular Health Study between 1989–1990 and 1997–1998, based on 15-ft walk (in seconds), grip strength (in kilograms), and chair stand (in seconds). In the 15-ft walk, a trained examiner measured the time needed for participants to walk a 15-ft course (4.5 m) at their usual pace. Grip strength in the dominant hand was measured using a hand-held JAMAR dynamometer, recording the force (in kilograms) for the best of three attempts at maximal squeeze. For chair stand, a trained examiner recorded how quickly each participant performed five consecutive chair stands (standing up, with arms folded across the chest, from a seated position on a 45-cm-tall chair), timed to the nearest tenth of 1 s. We evaluated each PF measure separately and, similar to the walking score, also constructed a summary measure based on all three PF measures (each in quintiles) to better capture the full variation of PF within the cohort.

Measurement of TL

TL (in kilo base pairs) was measured as the mean length of terminal restriction fragments in peripheral leukocytes (4,11,254,11,254,11,25). Five hundred eighty-two older adults who consented to DNA preparation and use, had at least 12 μg of available DNA, and had stored leukocytes for additional DNA preparation in both 1992–1993 and 1997–1998 were included in the present analysis of change in TL. TL was measured using Southern blot analysis, as previously described (3,253,25). Each sample was analyzed twice on different gels on different occasions, with the mean value used for statistical analyses. The Pearson correlation coefficient for these duplicates was 0.97 (mean coefficient of variation for pair sets, 1.5%). The laboratory conducting TL measurements was blinded to all participant characteristics.

DNA integrity was assessed through electrophoresis of 0.5 μg of DNA on 1.0 ethidium bromide. These measures suggested some degradation, which would attenuate the ability to detect differences in changes in TL across time, especially across only 5 yr (1992–1993 to 1997–1998).


Information on a wide range of covariates was obtained during study visits, including demographics, education, income, detailed smoking habits, alcohol use, usual dietary habits, body mass index (BMI), medication use, hypertension, diabetes, presence or absence of CHD, and presence or absence of congestive heart failure (13). BMI was calculated as weight (in kilograms)/height (in meters)2. Hypertension status was defined as either not present (systolic blood pressure <140 mm Hg, diastolic blood pressure <90 mm Hg, and no use of antihypertensive medication), borderline (systolic pressure of 140–159 mm Hg or diastolic pressure of 90–94 mm Hg and no use of antihypertensive medication), or definite (systolic pressure ≥160 mm Hg, diastolic pressure ≥95 mm Hg, or use of antihypertensive medication). Diabetes mellitus was classified using the criteria of the American Diabetes Association (21) (not present, impaired fasting glucose, definite diabetes). Myocardial infarction was diagnosed using an algorithm including cardiac symptoms (such as chest pain), abnormal cardiac enzyme concentrations, and serial electrocardiogram changes. Fatal CHD included deaths not meeting criteria for myocardial infarction but occurred within 72 h of chest pain or with a history of ischemic heart disease. CHD includes myocardial infarction, angina, angioplasty, bypass, and death due to atherosclerosis. Stroke was classified as ischemic (evidence of focal brain deficit without evidence of primary hemorrhage), hemorrhagic (bloody spinal fluid on lumbar puncture or evidence of blood in the subarachnoid space, ventricles, or parenchyma on brain imaging or at surgery or autopsy that did not appear consistent with hemorrhage into an infarction), or unknown (information was insufficient for classification) (19). CVD was defined as combined incidence of deaths due to stroke, fatal and nonfatal myocardial infarction, and CHD.

Statistical analysis

Cross-sectional associations of PA and PF with TL were assessed using multivariable repeated-measures linear regression, utilizing measures of TL in both 1992–1993 and 1997–1998 and accounting for within-person correlation. To minimize misclassification (measurement error) and to better represent long-term effects of habitual PA and PF, we took advantage of repeated measures of PA to PF to perform cumulative updating (averaging of serial values) (Figure, Supplemental Digital Content 1, Timeline assessment of physical activity and physical fitness and telomere length in the Cardiovascular Health Study between 1989–1990 and 1997–1998, When PA or PF was missing, existing values were carried forward. Cumulatively averaged PA and PF measures from 1989–1993 were related to TL in 1992–1993, and cumulatively averaged PA and PF from 1993–1998 were related to TL in 1997–1998. PA measures were assessed as categorical (indicator) variables, with tests for trend evaluated by entering PA categories as ordinal variables.

Longitudinal analyses of PA and PF with change in TL were assessed using multivariable linear regression. Cumulatively averaged PA and PF from 1989–1993 were related to the subsequent change in TL between 1992–1993 and 1997–1998; changes in cumulatively averaged PA and PF between 1989–1993 and 1993–1998 were related to changes in TL between 1992–1993 and 1997–1998. The rate of change in TL was calculated (in base pairs per year) as: (TL1997–1998 − TL1992–1993)/follow-up years.

To minimize confounding, we adjusted models for major demographic factors including age, sex, race, study enrollment site, education, income, smoking status, and usual dietary habits, including consumption of total energy, omega-3 polyunsaturated fatty acids, omega-6 polyunsaturated fatty acids, and dietary fiber (6,106,10). We also evaluated factors that could be plausible biologic intermediates (i.e., on the putative causal pathway between PA and TL), including, BMI, waist circumference, fasting glucose, insulin, inflammatory markers, and prevalent diseases including type 2 diabetes mellitus and CVD.

In additional analyses, we evaluated both PA and PF measures in the same model to assess their independent associations with TL. To minimize the possibility of reverse causation (poor health causing low PA/PF), we performed sensitivity analyses restricted to participants reporting only good, very good, or excellent overall health and having no limitation in activities of daily living or instrumental activities. Because the measured change in TL was positive in some participants (45%; potentially representing measurement error given that TL is not generally expected to increase), we also performed sensitivity analyses evaluating change in TL as a binary variable (any attrition; yes, no) and as a continuous variable but with any observed increases recoded as 0 (no change). We assessed potential interaction by age, sex, race, and BMI by including a cross-product term of each potential modifier and each PA/PF measure in the regression model, evaluating significance of interaction using Wald test. Analyses were performed using Stata 10.0 (StataCorp, College Station, TX; two-tailed alpha = 0.05).


At baseline, the mean ± SD age was 73 ± 5 yr, and 62% of participants were women (Table 1). About one in five participants had prevalent CHD, and one in seven participants had prevalent diabetes. Participants spent a mean ± SD of 1045 ± 1446 kcal·wk−1 on leisure-time activities, and 35% engaged in moderate-intensity PA. Participants walked a mean ± SD of 41 ± 65 blocks per week, with 67% having a pace faster than 2 mph. The mean ± SD time needed to complete a distance of 15 ft and five chair stands was 5.5 ± 2.0 and 14.8 ± 4.9 s, respectively. In addition, the mean ± SD hand grip strength was 27.5 ± 9.8 kg.

Baseline (1992–1993) characteristics of 582 older US adults in the Cardiovascular Health Study with longitudinal assessment of PA, PF, and TL.

Overall at baseline, TL ranged from 5.1 to 8.6 kb, with a mean ± SD of 6.3 ± 0.6 kb and a median of 6.3 kb. The mean ± SD change in TL (calculated as TL1997–1998 − TL1992–1993) was −0.012 ± 0.18 kb between 1992–1993 and 1997–1998, for an annualized attrition of −2.44 bp·yr−1.

Cross-sectional analysis of PA, PF, and TL

In cross-sectional multivariable-adjusted analyses, greater reported walking distance and better chair test performance were associated with longer TL (P trend = 0.007 and 0.04, respectively) (Table 2). In addition, a better overall fitness score was associated with a trend toward longer TL (P trend = 0.09). In contrast, walking pace, leisure-time activity, time to complete a 15-ft walk, and hand grip strength were not significantly associated with TL. Analysis included only participants with excellent, very good, and good health status; those with no limitations in activities of daily living or instrumental activities generated similar results.

Multivariable-adjusted cross-sectional associations of cumulatively averaged PA and PF between 1989–1990 and 1992–1993 and between 1993–1994 and 1997–1998 with TL from 1992 to 1993 and from 1997 to 1998 among 1164 older US adults.

Longitudinal analysis of PA and PF and change in TL

In multivariable longitudinal analyses, no significant associations between PA and PF from 1989–1993 and subsequent 5-yr change in TL were observed (Table 3). Results for participants with good or better health status and without limitations in activities of daily living or instrumental activities were generally similar. In secondary analyses evaluating change in TL as a binary variable (attrition; yes, no) or as a continuous variable but with any observed increases recoded as 0, no significant associations between PA and PF from 1989–1993 and subsequent 5-yr change in TL were observed (Tables, Supplemental Digital Content 2 and 3, Additional statistical analyses,,

Multivariable-adjusted longitudinal associations of cumulatively averaged PA and PF between 1989 and 1993 with changes in TL between 1992–1993 and 1997–1998 among 582 older US adults.

Longitudinal analysis of changes in PA and PA and change in TL

When we evaluated changes in PA and PF and changes in TL, change in leisure-time activity was associated with a trend toward less shortening in TL (P trend = 0.07), and change in chair test performance was associated with less shortening in TL (P trend = 0.04) (Table 4). For example, each 1000 kcal·wk−1 of increased leisure-time activity was associated with a trend toward less attrition (2.2 bp·yr−1; 95% CI, −0.18 to 4.6), and each 1-s change in the time needed to complete five chair stands was associated with 0.9 bp·yr−1 less attrition in TL (95% CI, 0.04 to 1.8). Other PA measures (such as walking pace, walking distance, and walking score) and other PF measures (such as walk test, hand grip test, and overall PF score) were not significantly associated with change in TL. When we excluded participants with poor self-reported health status or participants having any limitations in activities of daily living or instrumental activities, the associations of changes in leisure-time activity and chair test performance with change in TL were strengthened in magnitude (2.8 and 1.2 bp·yr−1, respectively) and statistical significance (P trend = 0.04 and 0.02, respectively). Results for sensitivity analyses recoding any observed increases in TL to no change were generally similar (Table, Supplemental Digital Content 4, Additional statistical analyses,

Multivariable-adjusted associations of changes in cumulatively averaged PA and PF between 1989–1993 and 1993–1998 with changes in TL between 1992–1993 and 1997–1998 among 582 older US adults.

Results of several sensitivity analyses were not appreciably altered, including further adjustment of both PA and PF measures to assess their independent associations with TL or further adjustment of baseline characteristics that could be either confounders or mediators of these relationships (see “Methods”). In addition, we performed cumulative averaging, with 50% weight given to the most recent PA/PF measure; results were similar to those for equal weight cumulative averaging (data not shown).


In this large prospective study of older adults (mean age at first measurement of TL, 73 yr), cross-sectional analyses suggested that greater walking distance and chair test performance are associated with longer TL. Furthermore, prospective analyses have shown that changes in leisure-time activity and chair test performance are associated with differences in changes in TL. The lack of prospective associations of other PA and PF metrics could be attributed to measurement error in TL due to DNA degradation, which would have diminished the ability to detect changes. Even so, even later in life, changes in certain PA and PF are associated with TL, suggesting that greater leisure-time activity and fitness could reduce leukocyte attrition among older adults.

Telomeres are caplike nucleoproteins at chromosome ends that protect genome from degradation and interchromosomal fusion (16,3516,35). In the normal cellular process, a small portion of telomeric DNA is lost with each cell division; when a limit length is achieved, a cell undergoes apoptosis (35). Normally with aging, chromosomes become increasingly impaired due to DNA damage, eventually leading to apoptotic signals and cell death; however, telomeres can prevent or delay such damage (16). It has been hypothesized that certain lifestyles factors may accelerate telomere shortening and consequently affect health, healthy aging, and longevity (35). Shorter TL is associated with several age-related diseases (39), including CVD and type 2 diabetes (11). Our findings of longer telomeres with some measures of greater PA and PF at baseline and less telomere attrition with some measures of changes in PA and PF longitudinally suggest that PA and PF could influence pathways related to TL. Such an effect could, for example, partly account for the beneficial associations of PA and PF with many age-related diseases (35,3935,39). The biologic plausibility of our findings is supported by the putative pathways of telomere loss, which are thought to be related to cumulative burdens of oxidative stress and inflammation (2,142,14), and by the pathways of benefits of regular PA, which include upregulation of antioxidant defense systems (15) and reduced chronic systemic inflammation (41). By these and other pathways, PA may reduce oxidative DNA damage (33,3933,39); for example, duration of exercise has been inversely correlated with biomarkers for DNA and telomere damage and with p16 expression, a biomarker for cellular aging (39). Interestingly, a bout of acute exercise increases production of free radicals, depending on intensity and duration (15). This pro-oxidant response may be necessary for the activation of beneficial antioxidant and other cellular defense systems (29), through which habitual long-term PA (such as that evaluated in this study) may lead to beneficial physiological adaptations (15).

Another possible explanatory pathway might be through upregulation of telomerase reverse transcriptase, which seems to occur after exercise (14). For example, mechanisms for the beneficial effects of omega-3 fatty acids and PA on survival after acute myocardial infarction could be related to elevation in telomerase expression, resulting in higher regeneration potential (31,4531,45). Although controversial, some evidence suggests that leucocyte TL could actually elongate across a decade (24); however, others believe that apparent elongation is mainly due to measurement error (40). There has been no consensus on this potential for telomere lengthening; further studies on this topic are needed.

In the present work, we observed similarities and differences in cross-sectional versus prospective analyses. In cross-sectional analyses, walking distance, but not leisure-time activity, was associated with longer TL. Conversely, in prospective analyses, leisure-time activity, but not walking distance, was associated with differences in changes in TL. Interestingly, chair test performance was associated with both cross-sectional and prospective analyses. The reasons for these specific associations are unknown, and our novel findings highlight the need to further investigate how different types of PA and different measures of PF may influence TL.

The American College of Sports Medicine and the American Heart Association recommend that older adults engage in at least 30 min of moderate PA on most days of the week (1). Our results support these general guidelines by suggesting that long-term PA may influence telomere dynamics later in life.

Previous studies of PA and TL have provided inconsistent results; only four studies were conducted in older adults (18,28,34,4718,28,34,4718,28,34,4718,28,34,47). Among these, one cross-sectional study of 2006 older Chinese participants reported no association between PA and TL (47); the other three studies, which were also cross-sectional but were conducted in much smaller samples (N = 32–204), found positive associations between PA and TL (18,28,3418,28,3418,28,34). Our results are consistent with these latter three cross-sectional studies and with other cross-sectional studies of middle-age and younger participants linking higher PA to longer TL (7,8,17,18,21,28,34,487,8,17,18,21,28,34,487,8,17,18,21,28,34,487,8,17,18,21,28,34,487,8,17,18,21,28,34,487,8,17,18,21,28,34,487,8,17,18,21,28,34,487,8,17,18,21,28,34,48). Our findings build upon and expand these previous results by evaluating both cross-sectional and longitudinal associations of PA, PF, and TL (including changes in both) in a well-established cohort of older US adults.

Our analysis had several strengths. Information on PA, PF, TL, and other risk factors was prospectively assessed using standardized methods. Participants were randomly selected and enrolled from Medicare eligibility lists in several US communities, providing a community-based sample of older adults. Serial measures of PA allowed for evaluation of cumulatively updated PA, reducing misclassification and providing a better measure of longer-term PA. Serial measures also allowed for a novel evaluation of how changes in PA relate to changes in TL. Prospective analyses and sensitivity analyses excluding less healthy participants reduced the potential for reverse causation, and adjustment for a wide range of covariates minimized the potential impact of confounding.

Potential limitations were also present. Measurement error in TL (in particular, change in TL) would diminish the ability to detect associations, which would cause underestimation of the magnitude and statistical significance of our findings. In addition, the TL quantification technique used is a less sensitive method for identifying subtle differences between individuals and requires high-quality DNA. We evaluated several different PA and PF indices, increasing the possibility of chance findings. However, several of our findings are consistent with those of other studies, and one could consider each PA or PF and TL association as a separate hypothesis. Borderline P values should be interpreted with caution, with careful attention to both internal consistency and biologic plausibility. PA measures were obtained from self-reports and may appropriately reflect relative ordering (ranking) of participants but not precise quantitative levels of energy expenditure. Although a range of covariates were available and evaluated as potential confounders and although findings from sensitivity analyses were similar, residual confounding due to unknown or incompletely measured factors cannot be excluded. The assessments of PA, PF, and TL were subject to random error and biologic variability, which would attenuate findings toward the null. The prospective associations of cumulatively updated PA with TL could also partly reflect the effects of PA earlier in life; in contrast, the associations of changes in PA with TL would not be confounded by PA at younger ages. Different participants had different numbers of exposure measures and, thus, possibly different precisions of exposure. Results were attained from older, predominantly White Americans and may not be directly generalizable to other populations. Furthermore, our results may only be generalized to leukocyte TL because it may not reflect TL dynamics in other tissues. Conversely, leukocyte TL is the most commonly measured TL metric and has been associated with diverse exposures and disease end points in prior studies.

In sum, our results suggest that greater walking distance and chair test performance are cross-sectionally associated with longer TL and that changes in leisure-time activity and chair test performance are associated with differences in changes in TL. These results suggest that PA and PF may play a role in the regulation of TL during the aging process.

The authors express their gratitude to the Cardiovascular Health Study participants. A full list of participating Cardiovascular Health Study investigators and institutions is available at

This research was supported by contracts HHSN268201200036C, HHSN268200800007C, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, and N01HC85086, and by grant U01HL080295 from the National Heart, Lung, and Blood Institute, with additional contributions from the National Institute of Neurological Disorders and Stroke. Additional support was provided by grant R01AG023629 from the National Institute on Aging.

Luisa Soares-Miranda is supported by the grant SFRH/BPD/76947/2011 funded by FCT (QREN - POPH - Type 4.1 -Advanced training, subsidized by the European Social Fund and national funds of MEC), PTDC/DES/099018/2008 - FCT/FCOMP-01- 0124-FEDER-009573, and The Research Centre in Physical Activity Health and Leisure is supported by FCT: UID/DTP/00617/2013. Fumiaki Imamura was supported by the Medical Research Council Epidemiology Unit (grant MC_UU_12015/5).

The funders had no role in the design or conduct of the study; in the collection, management, analysis, or interpretation of data; or in the preparation, review, or approval of the manuscript.

The results of the present study do not constitute endorsement by the American College of Sports Medicine.

The authors declare no conflicts of interest.


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