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Ramaiah P, Jamel Baljon K, Alsulami SA, Lindsay GM, Chinnasamy L. Diet quality indices and odds of metabolic dysfunction-associated fatty liver disease: a case-control study. Front Nutr 2024; 10:1251861. [PMID: 38260062 PMCID: PMC10800572 DOI: 10.3389/fnut.2023.1251861] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2023] [Accepted: 11/02/2023] [Indexed: 01/24/2024] Open
Abstract
Objectives There are only limited studies investigating the impact of dietary quality indicators, such as dietary quality index (DQI), dietary diversity score (DDS), and alternative healthy eating index (AHEI), on metabolic dysfunction-associated fatty liver disease (MASLD). Furthermore, these indicators may have different components that could lead to varying results. Therefore, this study aims to assess the nutritional quality indicators and their potential association with MASLD. Methods The study included 128 recently diagnosed MASLD patients and 256 controls aged between 20 and 60 years. The dietary intake of participants was evaluated using a validated semi-quantitative food frequency questionnaire that consisted of 168 items. In this study, the method used to evaluate dietary diversity was based on five main food groups, specifically bread and grains, vegetables, fruits, meat, and dairy. The AHEI-2010 was computed using data collected from the FFQ. Results After adjusting for confounders in the fully adjusted model, a significant negative correlation was observed between DDS and the risk of MASLD (OR 0.41, 95% CI 0.20, 0.97). Participants in the top quartile of AHEI had a 76% lower risk of MASLD compared with those in the bottom quartile after controlling for all potential confounders in the fully adjusted model (OR 0.24, 95% CI 0.12, 0.56). Conclusion The results of our study suggest that there is a significant association between adherence to a high-diversity diet and a reduced likelihood of developing MASLD. Similarly, we observed a similar association between adherence to the AHEI diet and a lower risk of MASLD.
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Affiliation(s)
| | | | - Sana A. Alsulami
- Faculty of Nursing, Umm Al-Qura University, Makkah, Saudi Arabia
| | - Grace M. Lindsay
- Faculty of Nursing, Umm Al-Qura University, Makkah, Saudi Arabia
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Zhong WF, Song WQ, Wang XM, Li ZH, Shen D, Liu D, Zhang PD, Shen QQ, Liang F, Nan Y, Xiang JX, Chen ZT, Li C, Li ST, Lv XG, Lin XR, Lv YB, Gao X, Kraus VB, Shi XM, Mao C. Dietary Diversity Changes and Cognitive Frailty in Chinese Older Adults: A Prospective Community-Based Cohort Study. Nutrients 2023; 15:3784. [PMID: 37686817 PMCID: PMC10490160 DOI: 10.3390/nu15173784] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 08/21/2023] [Accepted: 08/26/2023] [Indexed: 09/10/2023] Open
Abstract
Evidence for the effects of dietary diversity changes and cognitive frailty (CF) in the older adults is not clear. This study aimed to investigate the relationship between dietary diversity changes and CF in older adults Chinese. A total of 14,382 participants (mean age: 82.3 years) were enrolled. Dietary diversity scores (DDSs) were collected and calculated using a food frequency questionnaire. DDS changes between baseline and first follow-up were categorized into nine patterns. The associations between DDS changes and the incidence of CF were estimated using Cox proportional hazards models. During an 80,860 person-year follow-up, 3023 CF cases were identified. Groups with a decrease in DDS had increased CF risk compared with the high-to-high DDS group, with adjusted hazard ratios (HRs; 95% confidence intervals (Cis)) of 1.30 (1.06, 1.59), 2.04 (1.51, 2.74), and 1.81 (1.47, 2.22) for high-to-medium, high-to-low, and medium-to-low groups, respectively. Lower overall DDS groups were associated with greater CF risks, with HRs (95% CIs) of 1.49 (1.19, 1.86) for the low-to-medium group and 1.96 (1.53, 2.52) for the low-to-low group. Compared with the high-to-high group, significant associations with CF were found in other DDS change groups; HRs ranged from 1.38 to 3.12 for the plant-based DDS group and from 1.24 to 1.32 for the animal-based DDS group. Additionally, extreme and moderate declines in overall DDS increased CF risk compared with stable DDS, with HRs (95% CIs) of 1.67 (1.50, 1.86) and 1.13 (1.03, 1.24), respectively. In conclusion, among older adults, a declining or persistently low DDS and a moderately or extremely declining DDS were linked to higher incident CF. Plant-based DDS changes correlated more strongly with CF than animal-based DDS changes.
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Affiliation(s)
- Wen-Fang Zhong
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou 510515, China; (W.-F.Z.); (W.-Q.S.); (X.-M.W.); (Z.-H.L.); (D.S.); (D.L.); (P.-D.Z.); (Q.-Q.S.); (F.L.); (Y.N.); (Z.-T.C.); (C.L.); (S.-T.L.); (X.-G.L.); (X.-R.L.)
| | - Wei-Qi Song
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou 510515, China; (W.-F.Z.); (W.-Q.S.); (X.-M.W.); (Z.-H.L.); (D.S.); (D.L.); (P.-D.Z.); (Q.-Q.S.); (F.L.); (Y.N.); (Z.-T.C.); (C.L.); (S.-T.L.); (X.-G.L.); (X.-R.L.)
| | - Xiao-Meng Wang
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou 510515, China; (W.-F.Z.); (W.-Q.S.); (X.-M.W.); (Z.-H.L.); (D.S.); (D.L.); (P.-D.Z.); (Q.-Q.S.); (F.L.); (Y.N.); (Z.-T.C.); (C.L.); (S.-T.L.); (X.-G.L.); (X.-R.L.)
| | - Zhi-Hao Li
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou 510515, China; (W.-F.Z.); (W.-Q.S.); (X.-M.W.); (Z.-H.L.); (D.S.); (D.L.); (P.-D.Z.); (Q.-Q.S.); (F.L.); (Y.N.); (Z.-T.C.); (C.L.); (S.-T.L.); (X.-G.L.); (X.-R.L.)
| | - Dong Shen
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou 510515, China; (W.-F.Z.); (W.-Q.S.); (X.-M.W.); (Z.-H.L.); (D.S.); (D.L.); (P.-D.Z.); (Q.-Q.S.); (F.L.); (Y.N.); (Z.-T.C.); (C.L.); (S.-T.L.); (X.-G.L.); (X.-R.L.)
| | - Dan Liu
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou 510515, China; (W.-F.Z.); (W.-Q.S.); (X.-M.W.); (Z.-H.L.); (D.S.); (D.L.); (P.-D.Z.); (Q.-Q.S.); (F.L.); (Y.N.); (Z.-T.C.); (C.L.); (S.-T.L.); (X.-G.L.); (X.-R.L.)
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Pei-Dong Zhang
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou 510515, China; (W.-F.Z.); (W.-Q.S.); (X.-M.W.); (Z.-H.L.); (D.S.); (D.L.); (P.-D.Z.); (Q.-Q.S.); (F.L.); (Y.N.); (Z.-T.C.); (C.L.); (S.-T.L.); (X.-G.L.); (X.-R.L.)
- Department of Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Qiao-Qiao Shen
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou 510515, China; (W.-F.Z.); (W.-Q.S.); (X.-M.W.); (Z.-H.L.); (D.S.); (D.L.); (P.-D.Z.); (Q.-Q.S.); (F.L.); (Y.N.); (Z.-T.C.); (C.L.); (S.-T.L.); (X.-G.L.); (X.-R.L.)
- School of Nursing, Southern Medical University, Guangzhou 510515, China
| | - Fen Liang
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou 510515, China; (W.-F.Z.); (W.-Q.S.); (X.-M.W.); (Z.-H.L.); (D.S.); (D.L.); (P.-D.Z.); (Q.-Q.S.); (F.L.); (Y.N.); (Z.-T.C.); (C.L.); (S.-T.L.); (X.-G.L.); (X.-R.L.)
| | - Ying Nan
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou 510515, China; (W.-F.Z.); (W.-Q.S.); (X.-M.W.); (Z.-H.L.); (D.S.); (D.L.); (P.-D.Z.); (Q.-Q.S.); (F.L.); (Y.N.); (Z.-T.C.); (C.L.); (S.-T.L.); (X.-G.L.); (X.-R.L.)
- School of Nursing, Southern Medical University, Guangzhou 510515, China
| | - Jia-Xuan Xiang
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou 510515, China; (W.-F.Z.); (W.-Q.S.); (X.-M.W.); (Z.-H.L.); (D.S.); (D.L.); (P.-D.Z.); (Q.-Q.S.); (F.L.); (Y.N.); (Z.-T.C.); (C.L.); (S.-T.L.); (X.-G.L.); (X.-R.L.)
| | - Zi-Ting Chen
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou 510515, China; (W.-F.Z.); (W.-Q.S.); (X.-M.W.); (Z.-H.L.); (D.S.); (D.L.); (P.-D.Z.); (Q.-Q.S.); (F.L.); (Y.N.); (Z.-T.C.); (C.L.); (S.-T.L.); (X.-G.L.); (X.-R.L.)
| | - Chuan Li
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou 510515, China; (W.-F.Z.); (W.-Q.S.); (X.-M.W.); (Z.-H.L.); (D.S.); (D.L.); (P.-D.Z.); (Q.-Q.S.); (F.L.); (Y.N.); (Z.-T.C.); (C.L.); (S.-T.L.); (X.-G.L.); (X.-R.L.)
| | - Shi-Tian Li
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou 510515, China; (W.-F.Z.); (W.-Q.S.); (X.-M.W.); (Z.-H.L.); (D.S.); (D.L.); (P.-D.Z.); (Q.-Q.S.); (F.L.); (Y.N.); (Z.-T.C.); (C.L.); (S.-T.L.); (X.-G.L.); (X.-R.L.)
| | - Xiao-Gang Lv
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou 510515, China; (W.-F.Z.); (W.-Q.S.); (X.-M.W.); (Z.-H.L.); (D.S.); (D.L.); (P.-D.Z.); (Q.-Q.S.); (F.L.); (Y.N.); (Z.-T.C.); (C.L.); (S.-T.L.); (X.-G.L.); (X.-R.L.)
| | - Xiu-Rong Lin
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou 510515, China; (W.-F.Z.); (W.-Q.S.); (X.-M.W.); (Z.-H.L.); (D.S.); (D.L.); (P.-D.Z.); (Q.-Q.S.); (F.L.); (Y.N.); (Z.-T.C.); (C.L.); (S.-T.L.); (X.-G.L.); (X.-R.L.)
| | - Yue-Bin Lv
- National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China;
| | - Xiang Gao
- Department of Nutrition and Food Hygiene, School of Public Health, Institute of Nutrition, Fudan University, Shanghai 200433, China;
| | - Virginia Byers Kraus
- Division of Rheumatology, Department of Medicine, Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC 27701, USA;
| | - Xiao-Ming Shi
- National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China;
| | - Chen Mao
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou 510515, China; (W.-F.Z.); (W.-Q.S.); (X.-M.W.); (Z.-H.L.); (D.S.); (D.L.); (P.-D.Z.); (Q.-Q.S.); (F.L.); (Y.N.); (Z.-T.C.); (C.L.); (S.-T.L.); (X.-G.L.); (X.-R.L.)
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Du Q, Lu Y, Hu F, Feng X, Zhang Y, Li S, Zhang C, Zhang H, Zeng Y, Yao Y, Lu Z, Zhang W, Gao X. Dietary diversity and possible sarcopenia among older people in China: a nationwide population-based study. Front Nutr 2023; 10:1218453. [PMID: 37457980 PMCID: PMC10348914 DOI: 10.3389/fnut.2023.1218453] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2023] [Accepted: 06/05/2023] [Indexed: 07/18/2023] Open
Abstract
Background Sarcopenia is a common geriatric disease. Many dietary factors may contribute to the development of sarcopenia. Few studies have been conducted on dietary diversity and sarcopenia in Chinese older adults. Among a nationwide sample, the objective of this study is to assess the association between the dietary diversity score (DDS) and the prevalence of possible sarcopenia. We considered the different patterns of dietary diversity in relation to possible sarcopenia. Methods We conducted this analysis utilizing the cross-sectional data from the 2012, 2014, and 2018 waves of the Chinese longitudinal healthy longevity survey (CLHLS). A standard developed by the Asian Working Group for Sarcopenia 2019 (AWGS2019) was used to assess the possibility of sarcopenia. On the basis of the DDS generated by previous studies, we have constructed four new indicators as follows: total diet, animal-based diet, plant-based diet, and plant-based diet without the consumption of legume products and nuts. We used the generalized estimation equation (GEE) model to evaluate the associations between the DDS of the total diet, animal-based diet, plant-based diet, and plant-based diet without the intake of legume products and nuts and possible sarcopenia. These associations were statistically adjusted for a variety of potential confounders. Sensitivity analysis was performed by excluding some participants who were long-term bedridden, had Alzheimer's disease, or were terminally ill. Results The analysis included 6,624 participants (mean age 83.4 years at baseline). In our study, we found that participants with a higher DDS of the total diet (OR = 0.62; 95% CI: 0.51-0.77), animal-based diet (OR = 0.62; 95% CI: 0.49-0.79), and plant-based diet (OR = 0.64;95% CI: 0.51-0.80) were at a lower risk of developing sarcopenia. In sensitivity analyses, the associations remained unchanged. Conclusion Taking a diversified diet, including animal foods, may reduce the risk of developing sarcopenia. According to the findings of this study, adopting a diversified diet might reduce the risk of sarcopenia for older adults.
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Affiliation(s)
- Qiaoqiao Du
- Health Management Center, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Yanhui Lu
- Department of Endocrinology, The Second Medical Center & National Clinical Research Center for Geriatric Disease, Chinese PLA General Hospital, Beijing, China
| | - Fan Hu
- Department of Endocrinology, The Second Medical Center & National Clinical Research Center for Geriatric Disease, Chinese PLA General Hospital, Beijing, China
| | - Xinglin Feng
- Department of Health Policy and Management, School of Public Health, Peking University, Beijing, China
| | - Yunquan Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University of Science and Technology, Wuhan, China
| | - Shaojie Li
- China Center for Health Development Studies, Peking University, Beijing, China
| | - Chi Zhang
- The Key Laboratory of Geriatrics, Institute of Geriatric Medicine, Chinese, Academy of Medical Sciences, National Center of Gerontology of National Health Commission, Beijing, China
| | - Hua Zhang
- Research Center of Clinical Epidemiology, Peking University Third Hospital, Beijing, China
| | - Yi Zeng
- Center for Healthy Aging and Development Studies, National School of Development, Peking University, Beijing, China
| | - Yao Yao
- China Center for Health Development Studies, Peking University, Beijing, China
| | - Zhaohui Lu
- Health Management Center, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Wenya Zhang
- Health Management Center, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Xiangyang Gao
- Health Management Institute, The Second Medical Center & National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
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