Issue 8, 2023

Association between the intake of animal offal and depressive symptoms: a TCLSIH cohort study

Abstract

Background: Previous cohort studies on the association between animal offal intake and depressive symptoms are limited, especially in Asian populations. This study aimed to prospectively investigate the association between animal offal intake and the risk of depressive symptoms in a general Chinese adult population. Methods: This prospective cohort study included a total of 7745 (57.6% males) inhabitants living in Tianjin, China. Participants without a history of CVD, cancer, and depressive symptoms at the baseline were followed up for 1.5 to 5 years with a median of 3 years follow-up. Animal offal was assessed using a validated self-administered food frequency questionnaire. Depressive symptoms were evaluated using the Chinese version of the Zung Self-Rating Depression Scale (SDS) and the cutoff score was set at 45. Cox proportional hazards regression models were used to estimate the association between animal offal intake and depressive symptoms. Results: A total of 1101 (630 men) people developed depressive symptoms during 19 074 person-years of follow-up. After adjusting for several potential confounders and setting “almost never” as the control group, the multivariable hazard ratios (95% confidence intervals) of the depressive symptoms were 0.96 (0.81, 1.15) for tertile 1, 1.04 (0.87, 1.24) for tertile 2, and 1.34 (1.13, 1.58) for tertile 3, respectively (P for trend <0.001). Conclusion: The results from our prospective study demonstrated that the intake of animal offal is positively associated with depressive symptoms.

Graphical abstract: Association between the intake of animal offal and depressive symptoms: a TCLSIH cohort study

Supplementary files

Article information

Article type
Paper
Submitted
31 Oct 2022
Accepted
06 Mar 2023
First published
08 Mar 2023

Food Funct., 2023,14, 3722-3731

Association between the intake of animal offal and depressive symptoms: a TCLSIH cohort study

H. Wu, Y. Gu, G. Meng, Q. Zhang, L. Liu, H. Wu, S. Zhang, X. Wang, J. Zhang, S. Sun, X. Wang, M. Zhou, Q. Jia, K. Song, H. Chang and K. Niu, Food Funct., 2023, 14, 3722 DOI: 10.1039/D2FO03311A

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