The prevalence and associated factors of skin tears in Belgian nursing homes: A cross-sectional observational study

J Tissue Viability. 2019 May;28(2):100-106. doi: 10.1016/j.jtv.2019.01.003. Epub 2019 Feb 7.


Background: Although skin tears are among the most prevalent acute wounds in nursing homes, their recognition as a unique condition remains in its infancy. Elderly patients are at risk of developing skin tears due to increased skin fragility and other contributing risk factors. In order to provide (cost-) effective prevention, patients at risk should be identified in a timely manner.

Objectives: (1) To determine the point prevalence of skin tears and (2) to identify factors independently associated with skin tear presence in nursing home residents.

Methods: A cross-sectional observational study was set up, including 1153 residents in 10 Belgian nursing homes. Data were collected by trained researchers and study nurses using patient records and skin observations. A multiple binary logistic regression model was designed to explore independent associated factors (significance level α < 0.05).

Results: The final sample consisted of 795 nursing home residents, of which 24 presented with skin tears, resulting in a point prevalence of 3.0%. Most skin tears were classified as category 3 (defined as complete flap loss) according to the International Skin Tear Advisory Panel (ISTAP) Classification System and 75.0% were located on the lower arms/legs. Five independent associated factors were identified: age, history of skin tears, chronic use of corticosteroids, dependency for transfers, and use of adhesives/dressings.

Conclusions: This study revealed a skin tear prevalence of 3.0% in nursing home residents. Age, history of skin tears, chronic use of corticosteroids, dependency for transfers, and use of adhesives/dressings were independently associated with skin tear presence.

Keywords: Associated factor; Elderly; Prevalence; Prevention; Skin integrity; Skin tear.

Publication types

  • Observational Study

MeSH terms

  • Aged
  • Aged, 80 and over
  • Belgium
  • Cross-Sectional Studies
  • Female
  • Humans
  • Logistic Models
  • Male
  • Nursing Homes / organization & administration
  • Nursing Homes / statistics & numerical data*
  • Prevalence
  • Risk Factors
  • Skin / injuries*