There is considerable interest in the research community when it comes to answering questions about the effects of exercise and inactivity on long-term health, pace of aging, and mortality. Possibly more than the topic merits now that rejuvenation therapies and other advanced medical biotechnologies are plausible near future goals for development. Since the development of low-cost accelerometers of the sort now found in every mobile phone, the quality of data has improved to the point at which quite detailed questions on activity levels and health can be asked and potentially answered. For example, what is the dose-response curve for exercise, when measured in terms of outcomes such as incidence of age-related disease and mortality rates? Another topic that has attracted a lot of attention in the past few years is the degree to which sitting, or similar sedentary behavior, has a negative impact on health that is independent of exercise. The studies I've seen so far are divided on this question: is it the sitting or is it the overall inactivity that is harmful or correlated with harmful choices, such as a high calorie intake and putting on weight?
The challenge for many studies is that their datasets include only self-reported activity levels. As the accelerometer study linked below illustrates very well, there is enough of a difference between what people say they do and what they actually do when it comes to exercise, even given the best of intentions, to cause issues in statistical interpretation. One might go so far as to say that any study not using accelerometers should probably be treated with suspicion for anything other than the most general conclusions drawn from its data. We know that exercise is good, and we know that a completely sedentary life is about as bad as taking up smoking, but a self-reported study is no basis for establishing effects by dose, or more subtle relationships such as how the degree of periodic inactivity versus the degree of periodic activity affects health over the long term.
The study below uses average telomere length in white blood cells as a metric for age. This is on the whole a pretty terrible biomarker, with an age-related decline that only shows up in the statistics for large populations, and even there we find studies that fail to observe correlations in various groups. For individuals it is of a very dubious value. That said, it is probably passable for the purposes of this study, insofar as it can be used to make the primary point above about the problems of self-reported data. For preference I'd rather see researchers using DNA methylation biomarkers of physical age, but if that isn't in the dataset used, then not much can be done within the time and budget allotted other than to work with what you have.
It is worth recalling that what this telomere length measurement primarily reflects is immune system health, not aging. It only reflects age through the effects of age on the immune system and its constituent parts. New immune cells are created by stem cells with long telomeres, and lose a little of that length every time they divide. Average telomere length in this measurement is thus determined by (a) stem cell activity, which is known to decline with age, (b) the rate of division of immune cells, which depends on any number of factors, from infection to other forms of ill health to the age-related malfunctions of the immune system as a whole, and (c) the number of senescent immune cells lingering with very short telomeres instead of following their peers into self-destruction. Some of these latter factors are highly variable with circumstances and on a very short time frame, which is one of the reasons as to why this isn't such a great metric for individuals, and why one has to examine the data across a large number of people to observe declines over time.
Researchers report that elderly women who sit for more than 10 hours a day with low physical activity have cells that are biologically older by eight years compared to women who are less sedentary. The study found elderly women with less than 40 minutes of moderate-to-vigorous physical activity per day and who remain sedentary for more than 10 hours per day have shorter telomeres - tiny caps found on the ends of DNA strands, like the plastic tips of shoelaces, that protect chromosomes from deterioration and progressively shorten with age. As a cell ages, its telomeres naturally shorten and fray, but health and lifestyle factors, such as obesity and smoking, may accelerate that process. Shortened telomeres are associated with cardiovascular disease, diabetes and major cancers. "Our study found cells age faster with a sedentary lifestyle. Chronological age doesn't always match biological age."
Nearly 1,500 women, ages 64 to 95, participated in the study. The women are part of the larger Women's Health Initiative (WHI), a national, longitudinal study investigating the determinants of chronic diseases in postmenopausal women. The participants completed questionnaires and wore an accelerometer on their right hip for seven consecutive days during waking and sleeping hours to track their movements. "We found that women who sat longer did not have shorter telomere length if they exercised for at least 30 minutes a day, the national recommended guideline. Discussions about the benefits of exercise should start when we are young, and physical activity should continue to be part of our daily lives as we get older, even at 80 years old."
Emerging evidence has linked leukocyte telomere length (LTL) to modifiable factors such as smoking, body mass index, and physical activity. Sedentary behavior has also been studied in relation to LTL, but with mixed findings. In the Nurses' Health Study, there was no association of total sedentary time or specific sedentary behaviors with LTL, but in 2 recent studies, reduced sedentary time was associated with longer LTL. However, these studies were limited by several factors, including failure to measure sedentary time objectively (i.e., by accelerometer). Accelerometer-measured sedentary time is not highly correlated with self-reported time, the latter of which often underestimates actual time spent in sedentary behaviors. In a cross-sectional study, we assessed associations of accelerometer-measured and self-reported sedentary time with LTL in older white and African-American women from the Objective Physical Activity and Cardiovascular Health (OPACH) Study, an ancillary study of the Women's Health Initiative (WHI).
In the overall sample, there were 863 (58.3%) white and 618 (41.7%) African-American women. Women were aged 79.2 years, on average, ranging in age from 64 years to 95 years. Women wore the accelerometer for an average of 14.7 hours/day over an average of 6.3 days. The mean amounts of accelerometer-measured and self-reported sedentary time were 9.2 hours/day and 8.6 hours/day, respectively. The mean amounts of accelerometer-measured and self-reported moderate- to vigorous-intensity physical activity (MVPA) were 0.8 hours/day and 0.5 hours/day, respectively. Accelerometer-measured and self-reported sedentary time were weakly correlated; accelerometer-measured and self-reported MVPA were similarly weakly correlated. Women with greater amounts of accelerometer-measured sedentary time were more likely to be older, white, and obese. They were also more likely to have high blood pressure, a history of chronic diseases, a lower physical performance score, and fewer hours/day of MVPA and to have experienced a fall in the past 12 months. Women with higher self-reported sedentary time were more likely to be older, white, and obese and to have a history of chronic diseases. They also had a lower physical performance score and lower levels of self-reported MVPA, and they were less likely to be in excellent or very good health.
Among older women who were less physically active as measured by accelerometry, a greater amount of accelerometer-measured sedentary time was significantly associated with shorter LTL. Findings persisted after adjustment for demographic characteristics, lifestyle behaviors, and body mass index but were attenuated after adjustment for a history of chronic diseases and use of hormone therapy. In the full-adjustment model, LTL was on average 170 base pairs shorter in the most sedentary women compared with the least sedentary women. Since women may lose on average 21 base pairs/year, this suggests that the most sedentary women were biologically older by 8 years. Our findings have important implications for an aging population, in which greater time spent sedentary and less physical activity tends to be the norm
Although we did not observe a significant statistical interaction between sedentary time and MVPA, several studies examining joint associations of sedentary time and physical activity with adverse health outcomes have observed that disease and mortality incidence risks associated with higher sedentary time were either attenuated or eliminated among persons engaging in greater amounts of physical activity and were stronger in those with lower levels of physical activity. In our study, accelerometer-measured sedentary time was not associated with LTL among women who were more physically active. Additionally, sedentary time was not associated with LTL among women meeting current public health recommendations of ≥30 minutes/day of MVPA; in those not meeting this recommendation, higher sedentary time was associated with shorter LTL.