“Skeletal Age” — a new idea for fracture risk assessment

It is my great pleasure to introduce my latest work [1] concerning the relationship between fracture and mortality. In this paper we wanted to redefine the concept of fracture risk that includes fracture risk and mortality risk, and to transform the risks into “Skeletal Age”.

We have known for some time that a bone fracture is associated with mortality. The risk of mortality after a hip fracture is increased by 2.9-fold (95% CI, 2.5 to 3.3) in women and 3.7-fold (3.3 to 4.1) in men. Moreover, about 30% of patients with a hip fracture will die within 12 months.

In the latest study, we followed more than 3500 men and women (all aged 60 years and older) to record the time of fracture, refracture, and mortality. We also measured their bone mineral density and other clinical risk factors. We then used mathematical model to define the transition between bone health states: from no fracture to fracture, from no fracture to mortality, from fracture to refracture, from fracture to mortality, etc. It is a complicated business, but math could handle that.

What did we find?

· We found that people affected by osteoporosis, particularly those suffered from a fracture, have shorter life expectancy than those without a fracture (about 2–10 years, depending on their risk profile), and the shortened life expectancy was greater in men than in women.

· Many people have multiple fractures. People with a first fracture tend to suffer another fracture within a shorter time period, and once a second fracture has occurred, their risk of death was accelerated.

· We then developed a tool to personalize the risk and time of refracture and mortality based on a person’s risk profile.

· Based on a person’s risk profile, we then calculate the skeletal age of the person. So, for example, a 70-year-old man with a fracture is predicted to have a skeletal age of 75.

Cumulative probability of mortality in women (left panel) and men (right panel) who had stayed in different states of bone health. There were 4 potential bone heath states before transiting to state 5 (i.e. mortality): State 1: No fracture (green blue colour area) if the individual entered the study without any osteoporotic fracture; State 2: initial fracture (light blue area) if an individual had sustained a fracture after study entry; State 3: Second fracture (purple-orange area) if an individual had suffered a second fracture; and State 4: Third & further fractures (red area) if an individual had suffered two or more subsequent fractures during the follow-up period. Risk was estimated for women and men with different BMD profiles (i.e. -1.5 vs -2.5), at the event age of 70 and 80, having all other factors set to the population mean, i.e. body mass index = 26.6 kg/m2, no history of fall at baseline, no prior fracture and no comorbidities.

Skeletal Age

So, in osteoporosis we have two types of risk: risk of fracture and refracture, and risk of death. The two risks are biologically and statistically linked. At present, we normally convey the risk of fracture to patients, but we don’t talk about the fact that once a fracture has occurred, their risk of death is increased substantially. The issue is how to convey this compound risk to patients and the general community.

I find the concept of “Effective Age” quite interesting. In engineering, effective age is defined as the age of a structure based on its current condition. Thus, for a perfectly maintained structure, its effective age is the same as its chronological age, but for a poorly maintained structure its effective age is older. Such a concept can also be applied to risk communication in medicine.

I propose that ‘skeletal age’ is the age of our skeleton as a result of a fracture. So, for a healthy individual without a fracture, the skeletal age is the same as the individual’s chronological age. However, because fracture is associated with an increased mortality, an individual with a pre-existing fracture is expected to have older skeletal age. The difference between chronological age and skeletal age can be used for conveying the impact of fracture to patients.

Thus, rather than telling patients that their risk of mortality increases by so and so, it may be more meaningful to tell them their skeletal age — the age they would be if they have a fracture. Telling a 60-year old patient with a hip fracture that his skeleton is that predicted for a 80-year old is likely to be more eye opening than tell him a 3-fold increase in mortality risk. Knowing skeletal age may help them to take preventive measure to mitigate his risk of post-fracture mortality.

The more difficult question is how to determine the skeletal age for an individual. Conceptually, the skeletal age of an individual can be defined as:

skeletal age = life expectancy + years gained/lost

where, “life expectancy” can be derived from the life table for age-and-sex specific population. For example, a 60-year old Australian is expected to live about 84 yr (if a man) or 87 yr (if a woman).

Brenner et al [2] have beautifully shown that the number of number of years lost or gained (denoted by Delta) is a simple function of the hazard ratio of mortality (HR) associated with a risk factor and the rate of mortality (Qx): Delta = log(HR) / log(Qx), where Qx is the probability that an individual who has lived to the age x dies before reaching age x + 1. It is fascinating that the Qx is almost a constant with actual value being round 1.1. In Australia, I have calculated that Qx is 1.093 for men and 1.10 for women aged 35 years and older. In other words, from age 35, the chance of dying before the next birth day increases by about 10% for each year we age. In practice, this relation means that in normal circumstances the average annual risk of death doubles for each log(2) / log(1.1) = 7 years of extra age. Remarkably, this increased risk is constant across populations [3].

Thus, the hazards of mortality associated with a risk factor can be seen as the difference between chronological age and ‘effective age’ (or ‘skeletal age’ in the present discussion).

Back to the idea of skeletal age for an individual with a hip fracture. A meta-analysis [4] has shown that a hip fracture increases an individual’s risk of death by 2.9-fold (for women) and 3.7-fold (for men). Thus, for a 60-year old man with a hip fracture, his skeletal age is roughly 60 + 15 = 75 years. In other words, the hip fracture has taken 15 years off his life expectancy.

The concept of skeletal age can also be used to quantify the beneficial effect of a treatment. Among women with a hip fracture, zoledronic acid reduces the risk of mortality by 28%, and this effect size is equivalent to a gain of approximately 3 years of life. Thus, for a woman with a hip fracture, her life expectancy is lost by ~11 years. However, if she is on zoledronate treatment, the years of life lost is reduced to ~8 years.

In summary, the concept of fracture risk should be redefined to combine the risk that an individual will sustain a fracture and the risk of mortality once a fracture has occurred. I do hope that the idea of skeletal age — together with the current Garvan Fracture Risk Calculator [5] — will help facilitate doctor — patient discussion about fracture vulnerability and treatment decisions.


[1] Thao Ho-Le et al. Epidemiological transition to mortality and re-fracture following an initial fracture. eLife 2021:

[2] Brenner H, Gefeller O, Greenland S. Risk and rate advancement periods as measures of exposure impact on the occurrence of chronic diseases. Epidemiology 1993;4:229–36.

[3] Vaupel JW. Biodemography of human ageing. Nature 2010;464:536–542.

[4] Haentjens P, et al. Meta-analysis: Excess Mortality After Hip Fracture Among Older Women and Men. Ann Int Med 2010;152:380–390.


osteoporosis | epidemiology | genetics | biostatistics | data enthusiast

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