Dietary patterns and multiple chronic diseases in older adults

Author:

Mao Danhui,Li Gongkui,Liang Moxuan,Wang Shiyun,Ren Xiaojun

Abstract

Abstract Background The prevalence rate of multiple chronic diseases among the elderly is relatively high, posing a risk to their health and also imposing a financial burden on them. Optimal dietary patterns have positive effects on multiple chronic diseases. This study aimed to identify dietary patterns associated with multiple chronic diseases in older adults. Methods Dietary intake was assessed through two non-consecutive 24-hour dietary recalls. The presence of multiple chronic diseases was assessed based on the existence of dyslipidemia, hypertension, chronic kidney disease, sleep disorders, diabetes, moderate or severe depressive symptoms, and cognitive impairment, with two or more of these conditions being considered. Latent class analysis was used to identify types of multiple chronic diseases, and two-step cluster analysis was used to determine individual dietary patterns. Logistic regression analysis with robust standard errors was conducted to determine the associations between dietary patterns and types of multiple chronic diseases. Results Three dietary patterns and three types of multiple chronic diseases were identified. Individuals following a diet rich in legumes, meat, vegetables and fruits (HLMVF dietary pattern) were 59% less likely to have the cardiometabolic cognitive impairment comorbidity (CCC) than those following a diet rich in milk and eggs but with low grain intake (HME-LG) (OR = 0.41, 95% CI: 0.27–0.64, P < 0.001) and 66% less likely to have the especially sleep disorders comorbidity (ESC) than those following a diet rich in grains but lacking milk and eggs (HG-LME) (OR = 0.34, 95% CI: 0.14–0.87, P < 0.05). Discussion The HLMVF dietary pattern may serve as a healthy dietary pattern to reduce the incidence of multiple chronic diseases and should be promoted among the older adult population.

Funder

the Doctorial Start-up Fund of Shanxi Medical University

the Science and Technology Innovation Projects of Higher Education Institutions in Shanxi Province

Publisher

Springer Science and Business Media LLC

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3