Dietary diversity and all-cause mortality among Chinese adults aged 65 or older: A community-based cohort study.

医学 混淆 饮食多样性 食品集团 队列研究 人口学 多样性(政治) 比例危险模型 队列 老年学 环境卫生 内科学 生物 生态学 社会学 人类学 粮食安全 农业
作者
Liyuan Tao,Zheng Xie,Tao Huang
出处
期刊:Asia Pacific Journal of Clinical Nutrition [Wiley]
卷期号:29 (1): 152-160 被引量:13
标识
DOI:10.6133/apjcn.202003_29(1).0020
摘要

Background and Objectives: To evaluate the association between dietary diversity and allcause mortality in older adults. Methods and Study Design: 17,949 community-based elderly participants aged ≥65 years in China were included in this cohort study. The baseline consumption frequencies of nine food groups (meat, vegetables, fish, eggs, fruits, legumes, milk, tea, and nuts) were recorded, and the dietary diversity score (0-9) was calculated. Survival status and death date were collected during follow-up. Cox proportional-hazards models were used to assess the association between dietary diversity and all-cause mortality. Results: We identified 8445 death events over 57,685 person-years of follow-up. Compared with participants in the lowest dietary diversity score group (score 0-1), higher dietary diversity scores were associated with lower mortality risk in univariate models. After adjusting for potential confounders, participants in the higher dietary diversity score group had a 9%-30% lower risk in all-cause mortality (p trend <0.001) compared with those in the lowest dietary diversity score group. The inverse relationship between dietary diversity score and all-cause mortality was also significant in four food groups (vegetables, fish, fruits, and nuts). Similar results were observed in sensitivity analyses. Conclusions: Our study showed that dietary diversity was inversely associated with all-cause mortality in the Chinese elderly, especially in the oldest old and men. Therefore, increasing dietary diversity may reduce mortality rates in the older population, and tailored interventions for improving dietary diversity are required to benefit health and survival in them.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
慕青应助科研通管家采纳,获得20
1秒前
大模型应助科研通管家采纳,获得10
1秒前
1秒前
1秒前
嘎嘣豆应助科研通管家采纳,获得10
1秒前
田様应助科研通管家采纳,获得10
1秒前
领导范儿应助科研通管家采纳,获得10
1秒前
1秒前
初景应助科研通管家采纳,获得10
1秒前
Xwu关闭了Xwu文献求助
1秒前
my196755发布了新的文献求助10
1秒前
思源应助科研通管家采纳,获得10
1秒前
Akim应助科研通管家采纳,获得10
1秒前
丘比特应助科研通管家采纳,获得10
1秒前
orixero应助科研通管家采纳,获得10
2秒前
2秒前
爆米花应助科研通管家采纳,获得10
2秒前
2秒前
2秒前
元谷雪发布了新的文献求助10
5秒前
周佳慧完成签到 ,获得积分10
6秒前
心静如水发布了新的文献求助10
6秒前
呆萌安萱发布了新的文献求助10
6秒前
长颈鹿完成签到 ,获得积分10
8秒前
8秒前
9秒前
积极的糖豆完成签到 ,获得积分10
9秒前
尽我所有完成签到,获得积分10
12秒前
12秒前
14秒前
李健应助my196755采纳,获得10
15秒前
zning发布了新的文献求助10
15秒前
15秒前
幸运的果子狸完成签到,获得积分10
15秒前
15秒前
杨媛发布了新的文献求助10
17秒前
17秒前
18秒前
Tyf发布了新的文献求助10
18秒前
19秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
Various Faces of Animal Metaphor in English and Polish 800
Signals, Systems, and Signal Processing 610
Photodetectors: From Ultraviolet to Infrared 500
On the Dragon Seas, a sailor's adventures in the far east 500
Yangtze Reminiscences. Some Notes And Recollections Of Service With The China Navigation Company Ltd., 1925-1939 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6348547
求助须知:如何正确求助?哪些是违规求助? 8163549
关于积分的说明 17174365
捐赠科研通 5404969
什么是DOI,文献DOI怎么找? 2861881
邀请新用户注册赠送积分活动 1839626
关于科研通互助平台的介绍 1688936