Development of a Frailty Prediction Model Among Older Adults in China: A Cross-Sectional Analysis Using the Chinese Longitudinal Healthy Longevity Survey.
Xianping Tang, Dongdong Shen, Tian Zhou and 5 others
PMID 39526483WHAT IT FOUND
A simple model using age, living situation, sleep, exercise and other routine questions separated frail from non-frail older adults in China, but it has not yet been tested outside this dataset.
Key findings
01Among 9006 older adults analysed, 1857 (20.6%) were frail and 7149 (79.4%) were non-frail.
02After internal validation, the model's discrimination score was 0.830 on a 0.5 to 1.0 scale; the area under the curve was 0.831.
03Living in a nursing home was associated with higher frailty odds (OR 3.066), while living alone was associated with lower frailty odds (OR 0.581), compared with living with family.
STILL TO COME
How it was doneWhat they foundWhat it means for RNs
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What it does not show
The study is cross-sectional, so it cannot show that any risk factor caused frailty. The model was only internally validated in the same dataset and has not been tested in a new population or setting. Of 15,874 survey participants, 9006 were analysed after missing-data exclusions, so findings apply to those with complete data. The sample included 53% advanced-age adults, and the authors said frailty prevalence may be overestimated. Smoking and drinking appeared protective, but the authors suggested this may reflect people stopping because of poor health. The model did not include biomarkers, polypharmacy or other clinical measures.
Declared interests
The supplied text does not state author conflicts of interest. The publication metadata describes the work as non-U.S. government research support.
The easy way to misread this
Do not use the nomogram as a proven screening tool. It was developed and internally checked in the same Chinese survey data, not tested in a new population, and its associations do not prove cause.