Chinese researchers have found a way to determine how much people are biologically getting older with a simple urine test.

The study, published on Tuesday in open-access journal in Frontiers in Aging Neuroscience identified a substance indicating oxidative damage increases in urine as people get older.

Researchers described a way to easily measure levels of this marker in human urine samples that potentially provides a method to measure how much our body has aged biologically rather than chronologically.

Since everyone born in the same year has the same chronological age, but the bodies of different people age at different rates, so the test could help predict our risk of developing age-related disease, and even our risk of death.

"Oxygen by-products produced during normal metabolism can cause oxidative damage to biomolecules in cells, such as DNA and RNA," said the paper's co-author Cai Jianping from Beijing Hospital and the Key Laboratory of Geriatrics under Chinese Ministry of Health.

"As we age, we suffer increasing oxidative damage, and so the levels of oxidative markers increase in our body," Cai said.

One marker, namely 8-oxoGsn, resulted from oxidation of a crucial molecule in our cells called RNA. In previous studies in animals, Cai and colleagues found that 8-oxoGsn levels increase in urine with age.

In the new study, the researchers measured 8-oxoGsn in urine samples from 1,228 Chinese residents aged 2 to 90 years old, using a rapid analysis technique called ultra-high-performance liquid chromatography.

"We found an age-dependent increase in urinary 8-oxoGsn in participants 21 years old and older." said Cai.

Levels of 8-oxoGsn were roughly the same between men and women, except in post-menopausal women, who showed higher levels. This may have been caused by the decrease in estrogen levels that happens during menopause, as estrogen is known to have anti-oxidant effects.

The team's rapid analysis technique could be useful for large-scale aging studies, as it can process urine samples from up to 10 participants per hour.

This study was supported by the National Natural Science Foundation of China.