The Relationship Between Pain and Eating among Overweight and Obese Individuals with Osteoarthritis: An Ecological Momentary Study. (2014)

• Record Type: Journal Article
• Authors: Choi, Karmel W; Somers, Tamara J; Babyak, Michael A; Sikkema, Kathleen J; Blumenthal, James A; Keefe, Francis J
• Is Part Of: Pain research and management. Volume 2014(2014)
• Page Start: e159
• Page End: e163
• Publication Date: 2014
• Subjects: BMI -- Eating -- Ecological momentary assessments (EMA) -- Obesity -- Osteoarthritis -- Pain -- Weight; Pain -- Periodicals; Pain -- Treatment -- Periodicals; 616.0472
• DOI: 10.1155/2014/598382
• Languages: English
• ISSNs: 1203-6765

Abstract

Abstract : BACKGROUND: Osteoarthritis (OA) patients who are overweight or obese report higher levels of pain compared with their normal-weight OA counterparts. Evidence suggests that overweight or obese OA patients also experience pain relief from eating foods high in calories, fat or sugar. Eating to alleviate pain may be problematic because it can lead to additional weight gain, which may contribute to heightened pain. OBJECTIVES: To investigate the relationship between pain and food intake using ecological momentary assessments in a sample of 71 over-weight and obese OA patients. METHODS: Participants completed two consecutive days of diary entries in which they recorded their levels of pain, mood and food intake throughout the day. Data were analyzed using generalized estimating equations that modelled pain as a predictor of calorie, fat and sugar intake. All models were adjusted for sex, body mass index, negative mood, time and treatment history. RESULTS: Pain significantly predicted calorie (Z=2.57; P=0.01) and fat intake (Z=1.99; P=0.05). CONCLUSIONS: Using ecological momentary assessments as a novel approach, the present study provides preliminary data supporting a relationship between pain and food intake among overweight and obese OA patients. Continued advances in our understanding of the relationship between pain and eating behaviour may help to optimize intervention strategies for these patients.