## Hand Grip Strength

Inputs

### Background

Reference intervals and normative data are important in medicine sciences and clinical care to characterize measured data. A typical way to represent such reference intervals is to use percentile curves separated by gender and age bands based on a large population. In this way, a new measured value can be compared to most frequent values of this population.

### Problem

Reference intervals and normative data are traditionally available for anthropometry and within laboratories in order to decide whether measured values are out of range and to trigger actions if necessary. However, such data are not available for new phenotypes such as the hand grip strength that has been measured as part of LIFE Adult [1], a large epidemiological study. That makes it difficult to characterize such data on an individual level.

### Solution

We used data of the initial $10.000$ subjects out of the epidemiological study LIFE Adult that had both hands. The data was subsequently filtered such that only subjects remained that were in the following age range: $[40,80]$. The age boundaries have been chosen on purpose to guarantee the existence of enough data points for each age to allow for a proper analysis. An additional step filtered out implausible values comprising zero values as well as high three-figure values that were internally used as error codes. Finally all subjects that didn't have socioeconomic status information attached to them were also filtered out. This led to a data set of $8380$ remaining subjects in total. Based on this data set percentile curves were generated for each combination of the following properties:
• Sex
• Age
• Socioeconomic status
Using this curves it is possible to compare individual values to those of the filtered LIFE Adult population mentioned above. This may allow for drawing conclusions about a single individual in the future using research results based on this population.

### References

 [1] Loeffler, Markus, et al. "The LIFE-Adult-Study: objectives and design of a population-based cohort study with 10,000 deeply phenotyped adults in Germany." BMC public health 15.1 (2015): 691.

### Disclaimer

I understand that this tool is not approved as a medicinal product for clinical use, and I confirm that I will use this tool for research purposes only.
Mir ist bekannt, dass dieses Werkzeug keine Zulassung als Medizinprodukt für den klinischen Gebrauch besitzt, und ich bestätige, dieses Werkzeug nur zu Forschungszwecken zu gebrauchen.