Wearable accelerometers can track death risk among older adults better than patient surveys and other methods used by physicians, reveals a new study.

Based on these findings, the researchers say physicians could confidently use the devices' fitness profiles to help patients change unhealthy behaviors, increase physical activity and, potentially, extend healthy lifespans.
While their study is far from the first to report an association between physical activity and risk of death, the investigators say their findings, reported in the Oct. 15 issue of The Journal of Gerontology: Medical Sciences, is among the first to offer solid evidence that wearable activity trackers provide key predictors of mortality that outperform other measures.
"People can overestimate or underestimate on surveys how much and when they move, but wearable devices provide accurate data that cut through the bias and guesswork," says Jacek Urbanek, Ph.D., assistant professor of medicine at the Johns Hopkins University School of Medicine and a member of the research team. "The technology is readily available and relatively inexpensive, so it seems feasible to be able to incorporate recommendations for its use into a physician's practice."
"We've been interested in studying physical activity and how accumulating it in spurts throughout the day could predict mortality because activity is a factor that can be changed, unlike age or genetics," says Ciprian Crainiceanu, Ph.D., professor of biostatistics at the Johns Hopkins Bloomberg School of Public Health, who is also a member of the research team.
For the new study, the researchers focused on the total amount of physical activity, and times the participants were most active during the day.
After studying each individual variable associated with mortality -- including education, sedentary time, and ethnicity --, the researchers concluded that the total measure of physical activity accumulated during each day was the strongest predictor of five-year mortality, followed by age and moderate-to-vigorous activity. When comparing the data of a person who died within five years and a person who survived, researchers said they were able to correctly rank the mortality risk using accelerometers 30% more accurately than using information about smoking status and 40% better than using information about whether a person suffered a stroke or had cancer.
With a focus on fragmented activity, researchers also collected data for two-hour spans throughout the day in order to look at patterns in physical activities. Their analysis showed that physical activity -- or lack thereof -- between noon and 2 p.m. was the highest predictor of mortality risk, outperforming more commonly considered risk factors such as diabetes, cancer, and alcohol consumption.
The researchers caution that their study wasn't designed to establish cause and effect. However, they did note that their data suggests that being more sedentary during the day is linked with higher mortality.
"The most surprising finding was that a simple summary of measures of activity derived from a hip-worn accelerometer over a week outperformed well-established mortality risk factors such as age, cancer, diabetes, and smoking," says Ekaterina Smirnova, M.S., Ph.D., assistant professor of biostatistics at Virginia Commonwealth University and the lead author on the paper.
"While this study affirmed a link between physical activity and short-term mortality risk in an older population, the data don't guarantee that one's risk of mortality is going to be lower with more physical activity," noted Andrew Leroux, a Ph.D. candidate at Johns Hopkins and co-author of the study report. "However, our findings do indicate that an accurate measure of physical activity is a more reliable way for doctors and patients to assess physical activity and intervene to increase it as a potential way to improve health."
The researchers hope to use their data to help design clinical trials that could confirm the potential for physical activity to increase lifespan. One caveat to the study is that researchers aren't able to distinguish sedentary behavior from sleep or if someone has removed the device.
Source-Eurekalert
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