Adherence to physical activity in an unsupervised setting: Explanatory variables for high attrition rates among fitness center members

J Sci Med Sport. 2016 Nov;19(11):916-920. doi: 10.1016/j.jsams.2015.12.522. Epub 2016 Jan 28.


Objectives: To evaluate the attrition rate of members of a fitness center in the city of Rio de Janeiro and the potential explanatory variables for the phenomenon.

Design: An exploratory, observational study using a retrospective longitudinal frame.

Methods: The records of 5240 individuals, members of the fitness center between January-2005 and June-2014, were monitored for 12 months or until cancellation of membership, whichever occurred first. A Cox proportional hazard regression model was adjusted to identify variables associated to higher risk of 'abandonment' of activities. This study was approved by Southern Cross University's Human Research Ethics Committee (approval number: ECN-15-176).

Results: The general survival curve shows that 63% of new members will abandon activities before the third month, and less than 4% will remain for more than 12 months of continuous activity. The regression model showed that age, previous level of physical activity, initial body mass index and motivations related to weight loss, hypertrophy, health, and aesthetics are related to risk of abandonment. Combined, those variables represent an important difference in the probability to abandon the gym between individuals with the best and worse combination of variables. Even individuals presenting the best combination of variables still present a high risk of abandonment before completion of 12 months of fitness center membership.

Conclusions: Findings can assist in the identification of high risk individuals and therefore help in the development of strategies to prevent abandonment of physical activity practice.

Keywords: Chronic disease; Exercise; Survival analysis.

Publication types

  • Observational Study

MeSH terms

  • Adult
  • Body Mass Index*
  • Brazil
  • Exercise*
  • Female
  • Fitness Centers / statistics & numerical data*
  • Humans
  • Longitudinal Studies
  • Male
  • Motivation*
  • Proportional Hazards Models
  • Risk
  • Time Factors
  • Young Adult