Association between the empirical dietary inflammatory index and musculoskeletal pain in community-dwelling older adults: a cross-sectional study.

Rezaei, Mahshid; Tajary, Zahra; Esmaeily, Zahra; Eyvazkhani, Atefeh; Daei, Shahrzad; Dara, Marjan Mansouri; Rezaei, Mohaddeseh; Djazayeri, Abolghassem; Motlagh, Ahmadreza Dorosty

Objectives: Inflammation has been proposed to be one of the main causes of musculoskeletal pain. Diet is a lifestyle factor that plays an important role in managing inflammation; thus, we assessed the inflammatory potential of diets using the empirical dietary inflammatory index (EDII) to investigate the relationship between diet and musculoskeletal pain. Methods: This cross-sectional study included 212 elderly individuals who were selected from health centers in Tehran, Iran. Dietary intake was evaluated using a valid and reliable 147-item food frequency questionnaire. To measure the intensity of pain, a visual analogue scale was used. Multiple linear regression was applied to assess the association between the EDII and musculoskeletal pain. Results: In total, 62.7% and 37.3% of participants had mild and severe pain, respectively. The EDII values were 0.97±0.72 and 1.10±0.66, respectively, in those with mild and severe pain. A higher EDII score was associated with more intense musculoskeletal pain after adjusting for age and sex (β=0.20; 95% confidence interval [CI], 0.06--0.26; p<0.001), but not after adjustment for other confounders (β=-0.13; 95% CI, -1.54 to 0.60; p=0.39). Conclusion: Our findings indicated that higher dietary inflammation might not be associated with musculoskeletal pain in older adults. However, further investigations are required to confirm these findings.

IRAN; FOOD habits; PAIN measurement; CONFIDENCE intervals; INFLAMMATION; CROSS-sectional method; FOOD consumption; MULTIPLE regression analysis; ANTHROPOMETRY; DIET; VISUAL analog scale; RISK assessment; PHYSICAL activity; MUSCULOSKELETAL pain; INDEPENDENT living; DESCRIPTIVE statistics; CHI-squared test; QUESTIONNAIRES; DATA analysis software; DISEASE risk factors; DISEASE complications; OLD age

Osong Public Health & Research Perspectives, 2023, Vol 14, Issue 1, p51

2210-9099

Academic Journal

10.24171/j.phrp.2022.0194