Does pain predict interference with daily functioning and weight loss in an obese residential treatment-seeking population?

Amy Wachholtz, Martin Binks, Howard Eisenson, Ronette Kolotkin, Ayako Suzuki

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

Background: Pain may interfere with daily functioning in obese persons and also with outcomes during weight loss. We examined the relationship between pain and (1) interference with daily functioning (DFi) and (2) outcomes in an obese treatment-seeking population. Method: Participants were 386 patients entering a residential weight loss program (body mass index, 40.7± 10.12 kg/m2). We examined the relationships of demographic factors, pain types, and emotional status with both baseline DFi and short-term weight loss. Results: Regression analysis showed that overall, total pain scores significantly predicted DFi even after controlling for other confounders (p<.05). Leg pain, joint pain, and headache predicted DFi (p's<.05) among women. Among both men and women, depression severity predicted DFi (p s<.01). For the entire sample, there was an inverse bivariate relationship between total pain score and weight loss (p<.001). Joint pain and depression (among women) and age and depression (among men) predicted reduced weight loss (p's<.05). Conclusion: These results highlight the value of assessing both pain and emotional status for individuals undergoing weight loss treatment since these may interfere recommendations to increase activity.

Original languageEnglish
Pages (from-to)118-124
Number of pages7
JournalInternational Journal of Behavioral Medicine
Volume17
Issue number2
DOIs
StatePublished - Jun 2010

Keywords

  • Activity of daily living
  • Depression
  • Obesity
  • Pain
  • Physical activity
  • Physical function
  • Weight loss

Fingerprint Dive into the research topics of 'Does pain predict interference with daily functioning and weight loss in an obese residential treatment-seeking population?'. Together they form a unique fingerprint.

Cite this