The risk associated with ultra-processed food intake on depressive symptoms and mental health in older adults: a target trial emulation.

IF 8.3 1区 医学 Q1 MEDICINE, GENERAL & INTERNAL BMC Medicine Pub Date : 2025-03-24 DOI:10.1186/s12916-025-04002-4
Belayneh Mengist, Mojtaba Lotfaliany, Julie A Pasco, Bruno Agustini, Michael Berk, Malcolm Forbes, Melissa M Lane, Suzanne G Orchard, Joanne Ryan, Alice J Owen, Robyn L Woods, John J McNeil, Mohammadreza Mohebbi
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Abstract

Background: Longitudinal cohort studies across the lifespan suggest an association between ultra-processed food (UPF) and depression. However, the effect of UPF on depression and mental health in older adults has not been determined. Therefore, this study investigated the effect of UPF on depressive symptoms and mental health in community-dwelling older adults.

Methods: A pragmatic target trial was designed and emulated using the ASPirin in Reducing Events in the Elderly longitudinal data. Participants were community-dwelling older adults (≥ 70 years) in Australia. We specified and emulated the protocol of a two-arm randomised pragmatic clinical trial using the level of UPF consumption as the intervention. Greater than or equal to 4 servings of UPF per day was considered the intervention, with less than 4 servings per day the control. Dietary consumption was assessed using a mail-based diet screening questionnaire, and the level of food processing was classified based on the NOVA classification. The study outcomes were depressive symptoms, defined as a score of ≥ 8 on the Center for Epidemiological Studies Depression 10-item scale, and general mental health, defined by the mental component summary score of the Short Form-12. We applied inverse probability treatment weighting to balance confounders. Marginal structural models were employed to estimate the population-level average effect of intervention using generalised estimated equations.

Results: A total of 11,192 participants (3415 intervention and 7777 control) were eligible for the emulation. High UPF consumption at time zero was associated with an increased risk of depressive symptoms at follow-ups (RR: 1.10; CI: 1.04-1.18). The finding was consistent with sensitivity analyses; after excluding participants on antidepressants at time zero, the risk of depressive symptoms in the intervention group was increased by 11% compared to the control (RR: 1.11; 95% CI: (1.04-1.20)). Consumption of UPF adversely affected the mental component quality of life (β: - 0.40; CI: - 0.65 to - 0.15).

Conclusions: A higher level of UPF consumption was associated with a higher risk of depressive symptoms and adversely affected mental health among older adults.

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超加工食品摄入对老年人抑郁症状和心理健康的风险:一项目标试验模拟
背景:整个生命周期的纵向队列研究表明,超加工食品(UPF)与抑郁症之间存在关联。然而,UPF对老年人抑郁和心理健康的影响尚未确定。因此,本研究调查了UPF对社区居住老年人抑郁症状和心理健康的影响。方法:采用阿司匹林减少老年人事件的纵向数据,设计并模拟一项实用的目标试验。参与者为澳大利亚社区居住的老年人(≥70岁)。我们指定并模拟了一项采用UPF消费水平作为干预措施的双臂随机实用临床试验方案。每天超过或等于4份UPF被认为是干预,每天少于4份为对照组。膳食消费评估采用基于邮件的饮食筛选问卷,并根据NOVA分类对食品加工水平进行分类。研究结果为抑郁症状(定义为流行病学研究中心抑郁10项量表得分≥8分)和一般心理健康(定义为Short Form-12的心理成分总结得分)。我们应用逆概率处理加权来平衡混杂因素。边际结构模型采用广义估计方程估计干预的总体水平平均效果。结果:共有11,192人(干预组3415人,对照组7777人)符合模拟条件。零时间时高UPF消耗与随访时抑郁症状风险增加相关(RR: 1.10;置信区间:1.04—-1.18)。这一发现与敏感性分析一致;在排除了在零时服用抗抑郁药的参与者后,干预组出现抑郁症状的风险比对照组增加了11% (RR: 1.11;95% ci:(1.04-1.20)。UPF的消耗对精神成分的生活质量有不利影响(β: - 0.40;CI: - 0.65至- 0.15)。结论:较高水平的UPF消费与较高的抑郁症状风险相关,并对老年人的心理健康产生不利影响。
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来源期刊
BMC Medicine
BMC Medicine 医学-医学:内科
CiteScore
13.10
自引率
1.10%
发文量
435
审稿时长
4-8 weeks
期刊介绍: BMC Medicine is an open access, transparent peer-reviewed general medical journal. It is the flagship journal of the BMC series and publishes outstanding and influential research in various areas including clinical practice, translational medicine, medical and health advances, public health, global health, policy, and general topics of interest to the biomedical and sociomedical professional communities. In addition to research articles, the journal also publishes stimulating debates, reviews, unique forum articles, and concise tutorials. All articles published in BMC Medicine are included in various databases such as Biological Abstracts, BIOSIS, CAS, Citebase, Current contents, DOAJ, Embase, MEDLINE, PubMed, Science Citation Index Expanded, OAIster, SCImago, Scopus, SOCOLAR, and Zetoc.
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