Journal of Inflammation Research (Oct 2021)

Investigating Associations Between Depressive Symptoms and Anti-/Pro-Inflammatory Nutrients in an Elderly Population in Northern China: A Bayesian Kernel Machine Regression Approach

  • Li R,
  • Zhan W,
  • Huang X,
  • Zhang L,
  • Sun Y,
  • Zhang Z,
  • Bao W,
  • Ma Y

Journal volume & issue
Vol. Volume 14
pp. 5201 – 5213

Abstract

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Ruiqiang Li,1,&ast; Wenqiang Zhan,2,&ast; Xin Huang,1 Limin Zhang,1 Yan Sun,1 Zechen Zhang,1 Wei Bao,1 Yuxia Ma1 1Department of Nutrition and Food Hygiene, School of Public Health, Hebei Medical University, Hebei Province Key Laboratory of Environment and Human Health, Shijiazhuang, People’s Republic of China; 2School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Yuxia MaDepartment of Nutrition and Food Hygiene, School of Public Health, Hebei Medical University, Hebei Province Key Laboratory of Environment and Human Health, Shijiazhuang, People’s Republic of ChinaEmail [email protected]: The potential for dietary inflammation has been shown to be associated with a variety of chronic diseases. The relationship between the potential for dietary inflammation and depression in the elderly is unclear.Objective: This study aimed to exam the relationship between different nutrients and the risk of depression symptoms in the elderly.Methods: In total, 1865 elderly in northern China were investigated at baseline from 2018 to 2019 and followed up in 2020. We measured the baseline intake of 22 nutrients and used Least Absolute Shrinkage and Selection Operator(LASSO) regression analysis and Bayesian Kernel Machine Regression (BKMR) to explore the association between exposure to a variety of nutrients with different inflammatory potentials and the risk of depressive symptoms.Results: A total of 447 individuals (24.0%) were diagnosed with depressive symptoms. Through the lasso regression model, it was found that 11 nutrients are significantly related to the risk of depressive symptoms, of which 6 nutrients are pro-inflammatory nutrients (inflammation effect score> 0), and 5 are anti-inflammatory nutrients (inflammation effect score< 0). We incorporated the inflammatory effect scores of 11 nutrients into the BKMR model at the same time, and found that the overall inflammatory effect of 11 nutrients increased with the increase of total inflammatory scores, suggesting that the overall effect was pro-inflammatory. BKMR subgroup analysis shows that whether in the pro-inflammatory nutrient group or the anti-inflammatory nutrient group, multiple nutrients have a significant combined effect on depressive symptoms. By comparing the overall and group effects, we found that the inflammatory effects of the pro-inflammatory diet and the anti-inflammatory diet in the study’s diet are offset by each other (P< 0.005).Conclusion: We determined the combined effect of multiple nutrients of different inflammatory potential classifications on depressive symptoms in the elderly.Keywords: depression, anti-inflammatory, pro-inflammatory, elderly, Bayesian kernel machine regression approach

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