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Hojjati Kermani MA, Awlqadr FH, Talebi S, Mehrabani S, Ghoreishy SM, Wong A, Amirian P, Zarpoosh M, Moradi S. Ultra-processed foods and risk of declined renal function: a dose-response meta-analysis of 786,216 participants. JOURNAL OF HEALTH, POPULATION, AND NUTRITION 2025; 44:79. [PMID: 40098054 PMCID: PMC11916343 DOI: 10.1186/s41043-025-00799-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/04/2025] [Accepted: 02/20/2025] [Indexed: 03/19/2025]
Abstract
OBJECTIVES Earlier investigations have documented an association between elevated consumption of Ultra-Processed Foods (UPFs) and adverse renal outcomes. To explore this relationship further, we executed a comprehensive dose-response meta-analysis to examine the link between UPFs intake and the risk of declined renal function. SETTING A systematic search was completed utilizing the ISI Web of Science, Scopus, Embase as well as PubMed/MEDLINE databases (without any restrictions), up until September 5, 2024. Effect sizes of declined renal function were recalculated by applying a random effects model. The GRADE tool was adopted to assess the certainty of the evidence, while study quality and potential publication bias were examined via validated methods such as the Newcastle-Ottawa Scale, Egger's regression asymmetry and Begg's rank correlation test. RESULTS Thirty-three studies (comprising 786,216 participants) were incorporated in the quantitative analysis. The results demonstrated that a greater UPFs intake was significantly associated with an enhanced risk of declined renal function (RR = 1.16; 95% CI: 1.09, 1.23; I2 = 68.8%; p < 0.001; n = 37). Additionally, we observed that each 1-serving-per-day increase in UPFs consumption was associated to a 5% greater risk of reduced renal function (RR = 1.05; 95% CI: 1.02, 1.09; I2 = 80.9%; p = 0.013; n = 9). A positive, linear association between UPF intake and the risk of declined renal function (Pnonlinearity = 0.107, Pdose-response < 0.001) was further displayed in the non-linear dose-response analysis. CONCLUSION Greater exposure to UPFs is positively associated with the risk of declined renal function. The information emphasizes the importance of considering UPFs in the prevention and management of adverse renal outcomes.
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Affiliation(s)
- Mohammad Ali Hojjati Kermani
- Clinical Tuberculosis and Epidemiology Research Center, National Research Institute of Tuberculosis and Lung Diseases (NRITLD), Masih Daneshvari Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Farhang Hameed Awlqadr
- Department of Food Science and Quality Control, Halabja Technical College, Sulaimani Polytechnic University, Kurdistan Region, Iraq
| | - Sepide Talebi
- Student's Scientific Research Center (SSRC), Tehran University of Medical Sciences, Tehran, Iran
- Department of Clinical Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences, Tehran, Iran
| | - Sanaz Mehrabani
- Nutrition and Food Security Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Seyed Mojtaba Ghoreishy
- Department of Nutrition, School of Public Health, Iran University of Medical Sciences, Tehran, Iran
- Student Research Committee, School of Public Health, Iran University of Medical Sciences, Tehran, Iran
| | - Alexei Wong
- Department of Health and Human Performance, Marymount University, Arlington, VA, USA
| | - Parsa Amirian
- General Practitioner, Kermanshah University of Medical Sciences (KUMS), Kermanshah, Iran
| | - Mahsa Zarpoosh
- General Practitioner, Kermanshah University of Medical Sciences (KUMS), Kermanshah, Iran
| | - Sajjad Moradi
- Research Center for Evidence-Based Health Management, Maragheh University of Medical Sciences, Maragheh, Iran.
- Department of Nutrition and Food Sciences, Maragheh University of Medical Sciences, Maragheh, Iran.
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Chang X, Shih CC, Chen J, Lee AS, Tan P, Wang L, Liu J, Li J, Yuan JM, Khor CC, Koh WP, Dorajoo R. Predictive Capabilities of Polygenic Scores in an East-Asian Population-based Cohort: The Singapore Chinese Health Study. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2025:2025.02.13.25322249. [PMID: 39990559 PMCID: PMC11844607 DOI: 10.1101/2025.02.13.25322249] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/25/2025]
Abstract
Background Existing polygenic scores (PGS) are derived primarily from studies performed in European populations. It is still unclear how these perform in improving risk predictions in East-Asians. Methods We generated 2,173 PGSs from 519 traits and assessed their associations with 58 baseline phenotypes in the Singapore Chinese Health Study (SCHS), a prospective cohort of 23,622 middle-aged and older Chinese residing in Singapore. We used linear regression to evaluate PGS performances for quantitative traits by calculating the explained variance (r²). For dichotomized phenotypes, we employed logistic regression to estimate the area under the receiver operating characteristic curve (AUC) in predictive models. Results Overall, traits with higher heritability scores exhibited stronger associations with PGSs, while behavioural traits, for example sleep duration and hours spent watching TV, showed weaker associations. Height and type 2 diabetes (T2D) exhibited the largest SNP-based heritability estimates with the largest increments in explained variance and AUC, respectively, compared to phenotypic models. We explored the effect of T2D risk factors on the association between the T2D PGS (PGS003444) and incident T2D. The PGS association was significantly mediated and modified by hypertension ( P indirect =1.56×10 -18 , P interaction =1.11×10 -6 ) and body mass index (BMI, P indirect =1.25×10 -36 , P interaction =2.10×10 -3 ). The prediction ability of PGS003444 for incident T2D was stronger was stronger among individuals who were non-overweight without hypertension (AUC=0.774) than in overweight individuals with hypertension (AUC=0.709). Conclusions In conclusion, our study demonstrated the divergent ability of PGSs in predictions of complex traits, and showed that for certain traits, such as T2D, PGSs may have the potential for improving risk prediction and personalized healthcare.
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Ouyang W, Xiao B, Chen H, Fu L, Tang F, Marrone G, Liu X, Wu Y, Carrero JJ. Dietary quality and adherence to dietary recommendations in Chinese patients with chronic kidney disease. Front Nutr 2025; 12:1547181. [PMID: 39963666 PMCID: PMC11831048 DOI: 10.3389/fnut.2025.1547181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2024] [Accepted: 01/15/2025] [Indexed: 02/20/2025] Open
Abstract
Objectives There is a lack of data regarding the quality of the diet and the adherence to dietary guidelines of patients with non-dialysis-dependent CKD (NDD-CKD) in China. Design and methods Single-center cross-sectional study of 261 patients with CKD stages 3-5, who responded to 3-day dietary records and undertook 24-h urine samples along with clinical, laboratory, and anthropometric assessments. We compared their food intake with Chinese recommendations for CKD patients, assessed dietary quality through the Chinese Healthy Eating Index (CHEI), and calculated the contribution to energy intake by processed foods according to the NOVA classification. Results Average energy intake was 30 ± 9 Kcal/kg/d, and 65% consumed less energy than recommended. The average protein intake was 1.2 ± 0.5 g/Kg/d, and 81% consumed more than recommended. 71% of patients consumed excess sodium and 80% consumed too little fiber. These proportions worsened across more severe CKD stages (all P trend value <0.05). The diet was considered of moderate quality (CHEI score 59.5 ± 11.0), and patients with CKD stages 4-5 scored progressively worse (P trend = 0.008). Total grains and tubers supplied 50 and 30% of the total energy and protein intake, respectively. Processed and ultra-processed foods contributed to 23.3% of dietary energy and 11.7% of food weight. Conclusion A large proportion of NDD-CKD at our center showed low adherence to diet recommendations. Although consumption of processed foods was low, diet quality worsened with more severe CKD, with low intake of whole grains, dairy, and soybean.
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Affiliation(s)
- Wenwei Ouyang
- Department of Global Public Health, Karolinska Institute, Stockholm, Sweden
- Key Unit of Methodology in Clinical Research, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine (Guangdong Provincial Hospital of Chinese Medicine), Guangzhou, China
| | - Bingjie Xiao
- The Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Huifen Chen
- The Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Lizhe Fu
- Chronic Disease Management Outpatient, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine (Guangdong Provincial Hospital of Chinese Medicine), Guangzhou, China
| | - Fang Tang
- Chronic Disease Management Outpatient, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine (Guangdong Provincial Hospital of Chinese Medicine), Guangzhou, China
| | - Gaetano Marrone
- Department of Global Public Health, Karolinska Institute, Stockholm, Sweden
| | - Xusheng Liu
- Department of Nephrology, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine (Guangdong Provincial Hospital of Chinese Medicine), Guangzhou, China
| | - Yifan Wu
- Chronic Disease Management Outpatient, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine (Guangdong Provincial Hospital of Chinese Medicine), Guangzhou, China
- Department of Nephrology, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine (Guangdong Provincial Hospital of Chinese Medicine), Guangzhou, China
| | - Juan Jesús Carrero
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
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Maroto-Rodriguez J, Ortolá R, Cabanas-Sanchez V, Martinez-Gomez D, Rodriguez-Artalejo F, Sotos-Prieto M. Diet quality patterns and chronic kidney disease incidence: a UK Biobank cohort study. Am J Clin Nutr 2025; 121:445-453. [PMID: 39667719 DOI: 10.1016/j.ajcnut.2024.12.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2024] [Revised: 12/03/2024] [Accepted: 12/05/2024] [Indexed: 12/14/2024] Open
Abstract
BACKGROUND Only a few studies have investigated the role of diet on the risk of chronic kidney disease (CKD) in European populations and have mainly focused on the Mediterranean diet. This is the first study to evaluate the association between various diet quality indices and CKD incidence in British adults. OBJECTIVE To study the relationship between a set of 6 different diet quality indices and CKD incidence among British adults. METHODS A prospective cohort with 106,870 participants from the UK Biobank, followed from 2009 to 2012 through 2021. Food consumption was obtained from ≥2 24-h dietary assessments. Dietary patterns were assessed using previously established indices: Alternate Mediterranean Index (aMED), Alternative Healthy Eating Index 2010, dietary approaches to stop hypertension (DASH), healthful plant-based diet index (hPDI), unhealthful plant-based diet index (uPDI), and dietary inflammatory index (DII). Incident CKD was obtained from clinical records, death registries, and self-reports. Analyses were performed with Cox regression models and adjusted for the main confounders. RESULTS After a median follow-up of 9.27 y, 2934 cases of CKD were ascertained. Hazard ratios (95% confidence interval) of CKD for the highest compared with lowest tertile of adherence to each diet score were 0.84 (0.76, 0.93) for aMED, 0.94 (0.85, 1.03) for alternative healthy eating index 2010, 0.77 (0.70, 0.85) for DASH, 0.79 (0.72, 0.87) for hPDI, 1.27 (1.16, 1.40) for uPDI, and 1.20 (1.18, 1.33) for DII. The results were robust in sensitivity analyses. CONCLUSIONS In British adults, higher adherence to the aMED, DASH, and hPDI patterns was associated with lower risk of CKD, whereas greater adherence to the uPDI and DII patterns was associated with greater risk.
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Affiliation(s)
- Javier Maroto-Rodriguez
- Department of Preventive Medicine and Public Health, School of Medicine, Universidad Autónoma de Madrid, Calle del Arzobispo Morcillo, Madrid, Spain
| | - Rosario Ortolá
- Department of Preventive Medicine and Public Health, School of Medicine, Universidad Autónoma de Madrid, Calle del Arzobispo Morcillo, Madrid, Spain; CIBERESP (CIBER of Epidemiology and Public Health), Madrid, Spain
| | - Veronica Cabanas-Sanchez
- Department of Preventive Medicine and Public Health, School of Medicine, Universidad Autónoma de Madrid, Calle del Arzobispo Morcillo, Madrid, Spain; CIBERESP (CIBER of Epidemiology and Public Health), Madrid, Spain; IMDEA-Food Institute, CEI UAM+CSIC, Madrid, Spain
| | - David Martinez-Gomez
- Department of Preventive Medicine and Public Health, School of Medicine, Universidad Autónoma de Madrid, Calle del Arzobispo Morcillo, Madrid, Spain; CIBERESP (CIBER of Epidemiology and Public Health), Madrid, Spain; IMDEA-Food Institute, CEI UAM+CSIC, Madrid, Spain
| | - Fernando Rodriguez-Artalejo
- Department of Preventive Medicine and Public Health, School of Medicine, Universidad Autónoma de Madrid, Calle del Arzobispo Morcillo, Madrid, Spain; CIBERESP (CIBER of Epidemiology and Public Health), Madrid, Spain; IMDEA-Food Institute, CEI UAM+CSIC, Madrid, Spain
| | - Mercedes Sotos-Prieto
- Department of Preventive Medicine and Public Health, School of Medicine, Universidad Autónoma de Madrid, Calle del Arzobispo Morcillo, Madrid, Spain; CIBERESP (CIBER of Epidemiology and Public Health), Madrid, Spain; IMDEA-Food Institute, CEI UAM+CSIC, Madrid, Spain; Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, United States.
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Mak RH, Iyengar A, Wang AYM. Nutrition Management for Chronic Kidney Disease: Differences and Special Needs for Children and Adults. Semin Nephrol 2023; 43:151441. [PMID: 37981474 DOI: 10.1016/j.semnephrol.2023.151441] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2023]
Abstract
Common goals of nutritional therapy across the spectrum of pediatric and adult chronic kidney disease (CKD) include maintaining normal body mass and composition and reducing associated morbidity and mortality. Adult nephrologists caring for children and adolescents may be challenged by the existing complexities in identifying and interpreting the nutritional status and growth in children. Pediatric nephrologists may face situations that call for a sound knowledge of assessing nutritional status and providing nutrition therapy for adolescents and young adults. One important additional nutrition goal in children is to achieve normal growth and development. Children are growing and therefore need more calories and nutrients than just maintaining their body weight and composition. Lack of weight and height gain actually is considered failure to thrive in children. Some fundamental differences in approaches to nutritional therapy in CKD are necessitated based on the etiology of CKD. A large proportion of adults with CKD are diabetics, so the approach would be a low-carbohydrate diet. Children with CKD, especially young ones, often are anorexic, so calorie supplements that could include quite a lot of carbohydrates often are prescribed. More adults with CKD have hypertension and atherosclerotic comorbidities, which result in recommendations for low-salt and low-fat diets. Children with CKD often have salt and electrolyte wasting disease states and would require normal- or even high-salt diets, and fats often are included in supplements to bolster calorie intake. Low-protein diets often are recommended in adults with predialysis CKD to slow disease progression. Children are growing and have a higher protein daily requirement. Low-protein diets have not been found to be efficacious in children with CKD, in achieving normal growth, or in slowing disease progression. Adult nephrologists caring for children and adolescents may be challenged by the existing complexities in identifying and interpreting nutritional status and growth in children. Pediatric nephrologists may face situations that call for a sound knowledge of assessing nutritional status and providing nutrition therapy for adolescents and young adults. This article discusses the differences in the assessment of nutritional status between children and adults, as well as provides a comprehensive approach to nutritional management for CKD across the age spectrum. Semin Nephrol 43:x-xx © 2023 Elsevier Inc. All rights reserved.
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Affiliation(s)
- Robert H Mak
- Division of Pediatric Nephrology, Rady Children's Hospital, University of California, San Diego, CA.
| | - Arpana Iyengar
- Department of Pediatric Nephrology, St John's Medical College Hospital, Bangalore, India
| | - Angela Yee-Moon Wang
- Department of Medicine, Queen Mary Hospital, The University of Hong Kong, Hong Kong Special Administrative Region, China
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Wang YJ, Du Y, Chen GQ, Cheng ZQ, Liu XM, Lian Y. Dose-response relationship between dietary inflammatory index and diabetic kidney disease in US adults. Public Health Nutr 2023; 26:611-619. [PMID: 35941082 PMCID: PMC9989711 DOI: 10.1017/s1368980022001653] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Revised: 05/30/2022] [Accepted: 07/19/2022] [Indexed: 11/06/2022]
Abstract
OBJECTIVE The impact of the dietary potential inflammatory effect on diabetic kidney disease (DKD) has not been adequately investigated. The present study aimed to explore the association between dietary inflammatory index (DII) and DKD in US adults. DESIGN This is a cross-sectional study. SETTING Data from the National Health and Nutrition Examination Survey (2007-2016) were used. DII was calculated from 24-h dietary recall interviews. DKD was defined as diabetes with albuminuria, impaired glomerular filtration rate or both. Logistic regression and restricted cubic spline models were adopted to evaluate the associations. PARTICIPANTS Data from the National Health and Nutrition Examination Survey (2007-2016) were used, which can provide the information of participants. RESULTS Four thousand two-hundred and sixty-four participants were included in this study. The adjusted OR of DKD was 1·04 (95 % CI 0·81, 1·36) for quartile 2, 1·24 (95 % CI 0·97, 1·59) for quartile 3 and 1·64 (95 % CI 1·24, 2·17) for quartile 4, respectively, compared with the quartile 1 of DII. A linear dose-response pattern was observed between DII and DKD (Pnonlinearity = 0·73). In the stratified analyses, the OR for quartile 4 of DII were significant among adults with higher educational level (OR 1·83, 95 % CI 1·26, 2·66) and overweight or obese participants (OR 1·67, 95 % CI 1·23, 2·28), but not among the corresponding another subgroup. The interaction effects between DII and stratified factors on DKD were not statistically significant (all P values for interactions were >0·05). CONCLUSIONS Our findings suggest that a pro-inflammatory diet, shown by a higher DII score, is associated with increased odd of DKD.
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Affiliation(s)
- Yong-Jun Wang
- Department of Health Management & Engineering Laboratory for Health Management, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jingshi Road 16766, Jinan250014, People’s Republic of China
- Department of Clinical Nutrition, Shandong Provincial Qianfoshan Hospital & The First Affiliated Hospital of Shandong First Medical University, Jinan, People’s Republic of China
| | - Yang Du
- Department of Health Management & Engineering Laboratory for Health Management, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jingshi Road 16766, Jinan250014, People’s Republic of China
| | - Guo-Qiang Chen
- Department of Health Management & Engineering Laboratory for Health Management, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jingshi Road 16766, Jinan250014, People’s Republic of China
- Department of Medical Record Management and Statistics, Shandong Provincial Qianfoshan Hospital & The First Affiliated Hospital of Shandong First Medical University, Jinan, People’s Republic of China
| | - Zhen-Qian Cheng
- Department of Health Management & Engineering Laboratory for Health Management, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jingshi Road 16766, Jinan250014, People’s Republic of China
- Department of Clinical Nutrition, Shandong Provincial Qianfoshan Hospital & The First Affiliated Hospital of Shandong First Medical University, Jinan, People’s Republic of China
| | - Xue-Mei Liu
- Department of Health Management & Engineering Laboratory for Health Management, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jingshi Road 16766, Jinan250014, People’s Republic of China
- Department of Clinical Nutrition, Shandong Provincial Qianfoshan Hospital & The First Affiliated Hospital of Shandong First Medical University, Jinan, People’s Republic of China
| | - Ying Lian
- Department of Health Management & Engineering Laboratory for Health Management, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jingshi Road 16766, Jinan250014, People’s Republic of China
- Department of Medical Record Management and Statistics, Shandong Provincial Qianfoshan Hospital & The First Affiliated Hospital of Shandong First Medical University, Jinan, People’s Republic of China
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Bishop NJ, Zhu J. A prospective cohort study of racial/ethnic variation in the association between change in cystatin C and dietary quality in older Americans. Br J Nutr 2023; 129:312-323. [PMID: 35403576 PMCID: PMC9870715 DOI: 10.1017/s0007114522001040] [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: 07/09/2021] [Revised: 03/14/2022] [Accepted: 03/22/2022] [Indexed: 02/03/2023]
Abstract
Using a sample of US adults aged 65 years and older, we examined the role of dietary quality in cystatin C change over 4 years and whether this association varied by race/ethnicity. The Health and Retirement Study provided observations with biomarkers collected in 2012 and 2016, participant attributes measured in 2012, and dietary intake assessed in 2013. The sample was restricted to respondents who were non-Hispanic/Latino White (n 789), non-Hispanic/Latino Black (n 108) or Hispanic/Latino (n 61). Serum cystatin C was constructed to be equivalent to the 1999-2002 National Health and Nutrition Examination Survey (NHANES) scale. Dietary intake was assessed by a semi-quantitative FFQ with diet quality measured using an energy-adjusted form of the Alternative Healthy Eating Index-2010 (AHEI-2010). Statistical analyses were conducted using autoregressive linear modelling adjusting for covariates and complex sampling design. Cystatin C slightly increased from 1·2 mg/l to 1·3 mg/l over the observational period. Greater energy-adjusted AHEI-2010 scores were associated with slower increase in cystatin C from 2012 to 2016. Among respondents reporting moderately low to low dietary quality, Hispanic/Latinos had significantly slower increases in cystatin C than their non-Hispanic/Latino White counterparts. Our results speak to the importance of considering racial/ethnic determinants of dietary intake and subsequent changes in health in ageing populations. Further work is needed to address measurement issues including further validation of dietary intake questionnaires in diverse samples of older adults.
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Affiliation(s)
- Nicholas J. Bishop
- Human Development and Family Sciences Program, School of Family and Consumer Sciences, Texas State University, San Marcos, TX78666, USA
| | - Jie Zhu
- Nutrition and Foods Program, School of Family and Consumer Sciences, Texas State University, San Marcos, TX78666, USA
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Lin IH, Wong TC, Duong TV, Nien SW, Tseng IH, Wang HH, Chiang YJ, Yang SH. Dietary quality indices and recurrent chronic kidney disease in Taiwanese post-renal transplant recipients. Front Nutr 2023; 9:1023000. [PMID: 36698465 PMCID: PMC9869263 DOI: 10.3389/fnut.2022.1023000] [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: 08/19/2022] [Accepted: 12/19/2022] [Indexed: 01/12/2023] Open
Abstract
Background This study investigated the association between dietary quality indices and recurrent chronic kidney disease (rCKD) in Taiwanese post-renal transplant recipients (RTRs). Methods This prospective study recruited RTRs aged >18 years with a functioning allograft and without any acute rejection in the past 3 months from September 2016 to June 2018. Dietary quality indices included the Alternative Healthy Eating Index (AHEI) and AHEI-2010, and the Taiwanese version of the AHEI (AHEI-Taiwan) was calculated using 3-day dietary records, and calculated scores were divided into quartiles. Laboratory data were collected from medical records. rCKD was defined as an estimated glomerular filtration rate (eGFR) of <60 mL/min/1.73 m2. Logistic regression analysis was performed to analyze the associations. Results This study included 102 RTRs. The RTRs with higher AHEI, AHEI-Taiwan, and AHEI-2010 scores were older and had higher eGFRs and lower odds of rCKD. As compared with the lowest quartile, patients with the highest quartiles of the AHEI [odds ratio (OR), 0.10; 95% confidence interval (95% CI): 0.02, 0.49; p-trend = 0.004), AHEI-2010 (OR, 0.17; 95% CI: 0.04, 0.72; p-trend = 0.016], and AHEI-Taiwan (OR, 0.13; 95% CI: 0.03-0.59; p-trend = 0.008) had lower odds of rCKD, respectively. As compared with the lowest quartile, patients who consumed the highest quartiles of red and processed meat had 11.43 times higher odds of rCKD (OR, 11.43; 95% CI: 2.30-56.85; p for trend <0.01). Conclusion Higher dietary quality indices are associated with lower odds of rCKD in Taiwanese RTRs. Particularly, a positive association between a higher intake of red meat and processed meat and higher odds of rCKD remained exists after transplantation in Taiwanese RTRs. Further dietary guidelines and individualized dietary education were necessary for RTRs to prevent graft function deterioration.
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Affiliation(s)
- I-Hsin Lin
- Department of Medical Nutrition Therapy, Linkou Chang Gung Memorial Hospital, Taoyuan, Taiwan,School of Nutrition and Health Sciences, College of Nutrition, Taipei Medical University, Taipei, Taiwan
| | - Te-Chih Wong
- Department of Nutrition and Health Sciences, Chinese Culture University, Taipei, Taiwan
| | - Tuyen Van Duong
- School of Nutrition and Health Sciences, College of Nutrition, Taipei Medical University, Taipei, Taiwan
| | - Shih-Wei Nien
- Department of Medical Nutrition Therapy, Linkou Chang Gung Memorial Hospital, Taoyuan, Taiwan
| | - I-Hsin Tseng
- Department of Medical Nutrition Therapy, Linkou Chang Gung Memorial Hospital, Taoyuan, Taiwan
| | - Hsu-Han Wang
- Department of Urology, Linkou Chang Gung Memorial Hospital, Taoyuan, Taiwan,School of Medicine, Chang Gung University, Taoyuan, Taiwan
| | - Yang-Jen Chiang
- Department of Urology, Linkou Chang Gung Memorial Hospital, Taoyuan, Taiwan,School of Medicine, Chang Gung University, Taoyuan, Taiwan
| | - Shwu-Huey Yang
- School of Nutrition and Health Sciences, College of Nutrition, Taipei Medical University, Taipei, Taiwan,Research Center of Geriatric Nutrition, College of Nutrition, Taipei Medical University, Taipei, Taiwan,Nutrition Research Center, Taipei Medical University Hospital, Taipei, Taiwan,*Correspondence: Shwu-Huey Yang,
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Geng T, Zhu K, Lu Q, Wan Z, Chen X, Liu L, Pan A, Liu G. Healthy lifestyle behaviors, mediating biomarkers, and risk of microvascular complications among individuals with type 2 diabetes: A cohort study. PLoS Med 2023; 20:e1004135. [PMID: 36626356 PMCID: PMC9831321 DOI: 10.1371/journal.pmed.1004135] [Citation(s) in RCA: 82] [Impact Index Per Article: 41.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Accepted: 10/26/2022] [Indexed: 01/11/2023] Open
Abstract
BACKGROUND The influence of overall lifestyle behaviors on diabetic microvascular complications remains unknown. In addition, the potential mediating biomarkers underlying the association is unclear. This study aimed to examine the associations of the combined lifestyle factors with risks of total and individual microvascular complications among patients with type 2 diabetes (T2D) and to explore the potential mediation effects of metabolic biomarkers. METHODS AND FINDINGS This retrospective cohort study included 15,104 patients with T2D free of macro- and microvascular complications at baseline (2006 to 2010) from the UK Biobank. Healthy lifestyle behaviors included noncurrent smoking, recommended waist circumference, regular physical activity, healthy diet, and moderate alcohol drinking. Outcomes were ascertained using electronic health records. Over a median of 8.1 years of follow-up, 1,296 cases of the composite microvascular complications occurred, including 558 diabetic retinopathy, 625 diabetic kidney disease, and 315 diabetic neuropathy, with some patients having 2 or 3 microvascular complications simultaneously. After multivariable adjustment for sociodemographic characteristics, history of hypertension, glycemic control, and medication histories, the hazard ratios (95% confidence intervals (CIs)) for the participants adhering 4 to 5 low-risk lifestyle behaviors versus 0 to 1 were 0.65 (0.46, 0.91) for diabetic retinopathy, 0.43 (0.30, 0.61) for diabetic kidney disease, 0.46 (0.29, 0.74) for diabetic neuropathy, and 0.54 (0.43, 0.68) for the composite outcome (all Ps-trend ≤0.01). Further, the population-attributable fraction (95% CIs) of diabetic microvascular complications for poor adherence to the overall healthy lifestyle (<4 low-risk factors) ranged from 25.3% (10.0%, 39.4%) to 39.0% (17.7%, 56.8%). In addition, albumin, HDL-C, triglycerides, apolipoprotein A, C-reactive protein, and HbA1c collectively explained 23.20% (12.70%, 38.50%) of the associations between overall lifestyle behaviors and total diabetic microvascular complications. The key limitation of the current analysis was the potential underreporting of microvascular complications because the cases were identified via electronic health records. CONCLUSIONS Adherence to overall healthy lifestyle behaviors was associated with a significantly lower risk of microvascular complications in patients with T2D, and the favorable associations were partially mediated through improving biomarkers of glycemic control, systemic inflammation, liver function, and lipid profile.
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Affiliation(s)
- Tingting Geng
- Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, Ministry of Education Key Lab of Environment and Health, and State Key Laboratory of Environment Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Kai Zhu
- Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, Ministry of Education Key Lab of Environment and Health, and State Key Laboratory of Environment Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Qi Lu
- Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, Ministry of Education Key Lab of Environment and Health, and State Key Laboratory of Environment Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhenzhen Wan
- Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, Ministry of Education Key Lab of Environment and Health, and State Key Laboratory of Environment Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xue Chen
- Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, Ministry of Education Key Lab of Environment and Health, and State Key Laboratory of Environment Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Liegang Liu
- Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, Ministry of Education Key Lab of Environment and Health, and State Key Laboratory of Environment Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - An Pan
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- * E-mail: (AP); (GL)
| | - Gang Liu
- Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, Ministry of Education Key Lab of Environment and Health, and State Key Laboratory of Environment Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- * E-mail: (AP); (GL)
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10
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Cecchini AL, Biscetti F, Rando MM, Nardella E, Pecorini G, Eraso LH, Dimuzio PJ, Gasbarrini A, Massetti M, Flex A. Dietary Risk Factors and Eating Behaviors in Peripheral Arterial Disease (PAD). Int J Mol Sci 2022; 23:10814. [PMID: 36142725 PMCID: PMC9504787 DOI: 10.3390/ijms231810814] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Revised: 09/10/2022] [Accepted: 09/13/2022] [Indexed: 11/17/2022] Open
Abstract
Dietary risk factors play a fundamental role in the prevention and progression of atherosclerosis and PAD (Peripheral Arterial Disease). The impact of nutrition, however, defined as the process of taking in food and using it for growth, metabolism and repair, remains undefined with regard to PAD. This article describes the interplay between nutrition and the development/progression of PAD. We reviewed 688 articles, including key articles, narrative and systematic reviews, meta-analyses and clinical studies. We analyzed the interaction between nutrition and PAD predictors, and subsequently created four descriptive tables to summarize the relationship between PAD, dietary risk factors and outcomes. We comprehensively reviewed the role of well-studied diets (Mediterranean, vegetarian/vegan, low-carbohydrate ketogenic and intermittent fasting diet) and prevalent eating behaviors (emotional and binge eating, night eating and sleeping disorders, anorexia, bulimia, skipping meals, home cooking and fast/ultra-processed food consumption) on the traditional risk factors of PAD. Moreover, we analyzed the interplay between PAD and nutritional status, nutrients, dietary patterns and eating habits. Dietary patterns and eating disorders affect the development and progression of PAD, as well as its disabling complications including major adverse cardiovascular events (MACE) and major adverse limb events (MALE). Nutrition and dietary risk factor modification are important targets to reduce the risk of PAD as well as the subsequent development of MACE and MALE.
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Affiliation(s)
- Andrea Leonardo Cecchini
- Internal Medicine, Università Cattolica del Sacro Cuore, Largo Francesco Vito 1, 00168 Rome, Italy
| | - Federico Biscetti
- Cardiovascular Internal Medicine, Fondazione Policlinico Universitario A. Gemelli IRCCS, Largo Agostino Gemelli 8, 00168 Rome, Italy
| | - Maria Margherita Rando
- Cardiovascular Internal Medicine, Fondazione Policlinico Universitario A. Gemelli IRCCS, Largo Agostino Gemelli 8, 00168 Rome, Italy
| | - Elisabetta Nardella
- Cardiovascular Internal Medicine, Fondazione Policlinico Universitario A. Gemelli IRCCS, Largo Agostino Gemelli 8, 00168 Rome, Italy
| | - Giovanni Pecorini
- Internal Medicine, Università Cattolica del Sacro Cuore, Largo Francesco Vito 1, 00168 Rome, Italy
| | - Luis H. Eraso
- Division of Vascular and Endovascular Surgery, Thomas Jefferson University, Philadelphia, PA 19107, USA
| | - Paul J. Dimuzio
- Division of Vascular and Endovascular Surgery, Thomas Jefferson University, Philadelphia, PA 19107, USA
| | - Antonio Gasbarrini
- Internal Medicine, Università Cattolica del Sacro Cuore, Largo Francesco Vito 1, 00168 Rome, Italy
- Department of Medical and Surgical Sciences, Fondazione Policlinico Universitario A. Gemelli IRCCS, Largo Agostino Gemelli 8, 00168 Rome, Italy
| | - Massimo Massetti
- Internal Medicine, Università Cattolica del Sacro Cuore, Largo Francesco Vito 1, 00168 Rome, Italy
- Department of Cardiovascular Sciences, Fondazione Policlinico Universitario A. Gemelli IRCCS, Largo Agostino Gemelli 8, 00168 Rome, Italy
| | - Andrea Flex
- Internal Medicine, Università Cattolica del Sacro Cuore, Largo Francesco Vito 1, 00168 Rome, Italy
- Cardiovascular Internal Medicine, Fondazione Policlinico Universitario A. Gemelli IRCCS, Largo Agostino Gemelli 8, 00168 Rome, Italy
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11
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Valle-Hita C, Díaz-López A, Becerra-Tomás N, Martínez-González MA, García VR, Corella D, Goday A, Martínez JA, Alonso-Gómez ÁM, Wärnberg J, Vioque J, Romaguera D, López-Miranda J, Estruch R, Tinahones FJ, Lapetra J, Serra-Majem L, Cano-Ibáñez N, Tur JA, Rubín-García M, Pintó X, Delgado-Rodríguez M, Matía-Martín P, Vidal J, Fontao SM, Daimiel L, Ros E, Toledo E, Sorlí JV, Roca C, Abete I, Moreno-Rodriguez A, Crespo-Oliva E, Candela-García I, Morey M, Garcia-Rios A, Casas R, Fernandez-Garcia JC, Santos-Lozano JM, Diez-Espino J, Ortega-Azorín C, Comas M, Zulet MA, Sorto-Sanchez C, Ruiz-Canela M, Fitó M, Salas-Salvadó J, Babio N. Prospective associations between a priori dietary patterns adherence and kidney function in an elderly Mediterranean population at high cardiovascular risk. Eur J Nutr 2022; 61:3095-3108. [PMID: 35366708 PMCID: PMC9363380 DOI: 10.1007/s00394-022-02838-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Accepted: 02/11/2022] [Indexed: 02/07/2023]
Abstract
PURPOSE To assess the association between three different a priori dietary patterns adherence (17-item energy reduced-Mediterranean Diet (MedDiet), Trichopoulou-MedDiet and Dietary Approach to Stop Hypertension (DASH)), as well as the Protein Diet Score and kidney function decline after one year of follow-up in elderly individuals with overweight/obesity and metabolic syndrome (MetS). METHODS We prospectively analyzed 5675 participants (55-75 years) from the PREDIMED-Plus study. At baseline and at one year, we evaluated the creatinine-based estimated glomerular filtration rate (eGFR) and food-frequency questionnaires-derived dietary scores. Associations between four categories (decrease/maintenance and tertiles of increase) of each dietary pattern and changes in eGFR (ml/min/1.73m2) or ≥ 10% eGFR decline were assessed by fitting multivariable linear or logistic regression models, as appropriate. RESULTS Participants in the highest tertile of increase in 17-item erMedDiet Score showed higher upward changes in eGFR (β: 1.87 ml/min/1.73m2; 95% CI: 1.00-2.73) and had lower odds of ≥ 10% eGFR decline (OR: 0.62; 95% CI: 0.47-0.82) compared to individuals in the decrease/maintenance category, while Trichopoulou-MedDiet and DASH Scores were not associated with any renal outcomes. Those in the highest tertile of increase in Protein Diet Score had greater downward changes in eGFR (β: - 0.87 ml/min/1.73m2; 95% CI: - 1.73 to - 0.01) and 32% higher odds of eGFR decline (OR: 1.32; 95% CI: 1.00-1.75). CONCLUSIONS Among elderly individuals with overweight/obesity and MetS, only higher upward change in the 17-item erMedDiet score adherence was associated with better kidney function after one year. However, increasing Protein Diet Score appeared to have an adverse impact on kidney health. TRIAL REGISTRATION NUMBER ISRCTN89898870 (Data of registration: 2014).
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Affiliation(s)
- Cristina Valle-Hita
- Department of Biochemistry and Biotechonology, Universitat Rovira i Virgili, Human Nutrition Unit, Carrer Sant Llorenç, 21, 43201, Reus, Spain
- Institut ďInvestigació Sanitària Pere Virgili (IISPV), 43204, Reus, Spain
- University Hospital of Sant Joan de Reus, Nutrition Unit, 43201, Reus, Spain
| | - Andrés Díaz-López
- Department of Biochemistry and Biotechonology, Universitat Rovira i Virgili, Human Nutrition Unit, Carrer Sant Llorenç, 21, 43201, Reus, Spain
- Institut ďInvestigació Sanitària Pere Virgili (IISPV), 43204, Reus, Spain
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERObn), Institute of Health Carlos III, 28029, Madrid, Spain
- Serra Hunter Fellow, Nutrition and Mental Health Research Group (NUTRISAM), Universitat Rovira i Virgili, 43201, Reus, Spain
| | - Nerea Becerra-Tomás
- Department of Biochemistry and Biotechonology, Universitat Rovira i Virgili, Human Nutrition Unit, Carrer Sant Llorenç, 21, 43201, Reus, Spain.
- Institut ďInvestigació Sanitària Pere Virgili (IISPV), 43204, Reus, Spain.
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERObn), Institute of Health Carlos III, 28029, Madrid, Spain.
- Department of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, Imperial College London, St Mary's Campus, Norfolk Place, London, W2 1PG, UK.
| | - Miguel A Martínez-González
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERObn), Institute of Health Carlos III, 28029, Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, IdiSNA, 31008, Pamplona, Spain
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Verónica Ruiz García
- Department of Biochemistry and Biotechonology, Universitat Rovira i Virgili, Human Nutrition Unit, Carrer Sant Llorenç, 21, 43201, Reus, Spain
- University Hospital of Tarragona Joan XXIII, 43005, Tarragona, Spain
| | - Dolores Corella
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERObn), Institute of Health Carlos III, 28029, Madrid, Spain
- Department of Preventive Medicine, University of Valencia, 46010, Valencia, Spain
| | - Albert Goday
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERObn), Institute of Health Carlos III, 28029, Madrid, Spain
- Cardiovascular Risk and Nutrition Research Group (CARIN), Hospital del Mar Research Institute (IMIM), Departament de Medicina, Universitat Autònoma de Barcelona, 08003, Barcelona, Spain
| | - J Alfredo Martínez
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERObn), Institute of Health Carlos III, 28029, Madrid, Spain
- Department of Nutrition, Food Science and Physiology, University of Navarra, IdiSNA, 31008, Pamplona, Spain
- Precision Nutrition Program, CEI UAM + CSIC, IMDEA Food and Health Sciences, 28049, Madrid, Spain
| | - Ángel M Alonso-Gómez
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERObn), Institute of Health Carlos III, 28029, Madrid, Spain
- Bioaraba Health Research Institute, Osakidetza Basque Health Service, Araba University Hospital, University of the Basque Country UPV/EHU, 01009, Vitoria-Gasteiz, Spain
| | - Julia Wärnberg
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERObn), Institute of Health Carlos III, 28029, Madrid, Spain
- Department of Nursing, University of Málaga, Institute of Biomedical Research in Malaga (IBIMA), 29071, Málaga, Spain
| | - Jesús Vioque
- Instituto de Investigación Sanitaria y Biomédica de Alicante, Miguel Hernandez University (ISABIAL-UMH), 46020, Alicante, Spain
- CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, 28029, Madrid, Spain
| | - Dora Romaguera
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERObn), Institute of Health Carlos III, 28029, Madrid, Spain
- Health Research Institute of the Balearic Islands (IdISBa), 07120, Palma de Mallorca, Spain
| | - José López-Miranda
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERObn), Institute of Health Carlos III, 28029, Madrid, Spain
- Department of Internal Medicine, Maimonides Biomedical Research Institute of Cordoba (IMIBIC), Reina Sofia University Hospital, University of Cordoba, 14004, Cordoba, Spain
| | - Ramon Estruch
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERObn), Institute of Health Carlos III, 28029, Madrid, Spain
- Department of Internal Medicine, Institutd'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Hospital Clinic, University of Barcelona, 08036, Barcelona, Spain
| | - Francisco J Tinahones
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERObn), Institute of Health Carlos III, 28029, Madrid, Spain
- Department of Endocrinology, Virgen de la Victoria Hospital Instituto de Investigación Biomédica de Málaga (IBIMA), University of Málaga, 29010, Málaga, Spain
| | - José Lapetra
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERObn), Institute of Health Carlos III, 28029, Madrid, Spain
- Department of Family Medicine, Research Unit, Distrito Sanitario Atención Primaria Sevilla, 41013, Sevilla, Spain
| | - Luís Serra-Majem
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERObn), Institute of Health Carlos III, 28029, Madrid, Spain
- Preventive Medicine Service, University of Las Palmas de Gran Canaria, Research Institute of Biomedical and Health Sciences (IUIBS), Centro Hospitalario Universitario Insular Materno Infantil (CHUIMI), Canarian Health Service, 35016, Las Palmas, Spain
| | - Naomi Cano-Ibáñez
- CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, 28029, Madrid, Spain
- Department of Preventive Medicine, University of Granada, 18071, Granada, Spain
| | - Josep A Tur
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERObn), Institute of Health Carlos III, 28029, Madrid, Spain
- Health Research Institute of the Balearic Islands (IdISBa), 07120, Palma de Mallorca, Spain
- Research Group On Community Nutrition and Oxidative Stress, University of Balearic Islands, 07122, Palma de Mallorca, Spain
| | - María Rubín-García
- Institute of Biomedicine (IBIOMED), University of León, 24071, León, Spain
| | - Xavier Pintó
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERObn), Institute of Health Carlos III, 28029, Madrid, Spain
- Lipids and Vascular Risk Unit, Internal Medicine, Hospital Universitario de Bellvitge-IDIBELL, Hospitalet de Llobregat, 08907, Barcelona, Spain
- University of Barcelona, 08007, Barcelona, Spain
| | - Miguel Delgado-Rodríguez
- CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, 28029, Madrid, Spain
- Division of Preventive Medicine, Faculty of Medicine, University of Jaén, 23071, Jaén, Spain
| | - Pilar Matía-Martín
- Department of Endocrinology and Nutrition, Instituto de Investigación Sanitaria Hospital Clínico San Carlos (IdISSC), 28040, Madrid, Spain
| | - Josep Vidal
- Departament of Endocrinology, IDIBAPS, Hospital Clínic, University of Barcelona, 08036, Barcelona, Spain
- CIBER Diabetes y Enfermedades Metabólicas (CIBERDEM), Instituto de Salud Carlos III (ISCIII), 28029, Madrid, Spain
| | - Sebastian Mas Fontao
- Department of Endocrinology and Nutrition, University Hospital Fundación Jimenez Díaz, Instituto de Investigaciones Biomédicas IISFJD, 28040, Madrid, Spain
| | - Lidia Daimiel
- CEI UAM + CSIC, Nutritional Control of the Epigenome Group, IMDEA Food, 28049, Madrid, Spain
| | - Emilio Ros
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERObn), Institute of Health Carlos III, 28029, Madrid, Spain
- Department of Endocrinology and Nutrition, Lipid Clinic, Hospital Clínic, Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), 08036, Barcelona, Spain
| | - Estefania Toledo
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERObn), Institute of Health Carlos III, 28029, Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, IdiSNA, 31008, Pamplona, Spain
| | - José V Sorlí
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERObn), Institute of Health Carlos III, 28029, Madrid, Spain
- Department of Preventive Medicine, University of Valencia, 46010, Valencia, Spain
| | - C Roca
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERObn), Institute of Health Carlos III, 28029, Madrid, Spain
- Cardiovascular Risk and Nutrition Research Group (CARIN), Hospital del Mar Research Institute (IMIM), Departament de Medicina, Universitat Autònoma de Barcelona, 08003, Barcelona, Spain
| | - Iztiar Abete
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERObn), Institute of Health Carlos III, 28029, Madrid, Spain
- Department of Nutrition, Food Science and Physiology, University of Navarra, IdiSNA, 31008, Pamplona, Spain
| | - Anai Moreno-Rodriguez
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERObn), Institute of Health Carlos III, 28029, Madrid, Spain
- Bioaraba Health Research Institute, Osakidetza Basque Health Service, Araba University Hospital, University of the Basque Country UPV/EHU, 01009, Vitoria-Gasteiz, Spain
| | - Edelys Crespo-Oliva
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERObn), Institute of Health Carlos III, 28029, Madrid, Spain
- Department of Nursing, University of Málaga, Institute of Biomedical Research in Malaga (IBIMA), 29071, Málaga, Spain
| | | | - Marga Morey
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERObn), Institute of Health Carlos III, 28029, Madrid, Spain
- Health Research Institute of the Balearic Islands (IdISBa), 07120, Palma de Mallorca, Spain
| | - Antonio Garcia-Rios
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERObn), Institute of Health Carlos III, 28029, Madrid, Spain
- Department of Internal Medicine, Maimonides Biomedical Research Institute of Cordoba (IMIBIC), Reina Sofia University Hospital, University of Cordoba, 14004, Cordoba, Spain
| | - Rosa Casas
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERObn), Institute of Health Carlos III, 28029, Madrid, Spain
- Department of Internal Medicine, Institutd'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Hospital Clinic, University of Barcelona, 08036, Barcelona, Spain
| | - Jose Carlos Fernandez-Garcia
- Department of Endocrinology, Virgen de la Victoria Hospital Instituto de Investigación Biomédica de Málaga (IBIMA), University of Málaga, 29010, Málaga, Spain
| | - José Manuel Santos-Lozano
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERObn), Institute of Health Carlos III, 28029, Madrid, Spain
- Department of Family Medicine, Research Unit, Distrito Sanitario Atención Primaria Sevilla, 41013, Sevilla, Spain
| | - Javier Diez-Espino
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERObn), Institute of Health Carlos III, 28029, Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, IdiSNA, 31008, Pamplona, Spain
- Atención Primaria, Servicio Navarro de Salud, Osasunbidea, Pamplona, Spain
| | - Carolina Ortega-Azorín
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERObn), Institute of Health Carlos III, 28029, Madrid, Spain
- Department of Preventive Medicine, University of Valencia, 46010, Valencia, Spain
| | - M Comas
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERObn), Institute of Health Carlos III, 28029, Madrid, Spain
- Cardiovascular Risk and Nutrition Research Group (CARIN), Hospital del Mar Research Institute (IMIM), Departament de Medicina, Universitat Autònoma de Barcelona, 08003, Barcelona, Spain
| | - M Angeles Zulet
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERObn), Institute of Health Carlos III, 28029, Madrid, Spain
- Department of Nutrition, Food Science and Physiology, University of Navarra, IdiSNA, 31008, Pamplona, Spain
| | - Carolina Sorto-Sanchez
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERObn), Institute of Health Carlos III, 28029, Madrid, Spain
- Bioaraba Health Research Institute, Osakidetza Basque Health Service, Araba University Hospital, University of the Basque Country UPV/EHU, 01009, Vitoria-Gasteiz, Spain
| | - Miguel Ruiz-Canela
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERObn), Institute of Health Carlos III, 28029, Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, IdiSNA, 31008, Pamplona, Spain
| | - Montse Fitó
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERObn), Institute of Health Carlos III, 28029, Madrid, Spain
- Cardiovascular Risk and Nutrition Research Group (CARIN), Hospital del Mar Research Institute (IMIM), Departament de Medicina, Universitat Autònoma de Barcelona, 08003, Barcelona, Spain
| | - Jordi Salas-Salvadó
- Department of Biochemistry and Biotechonology, Universitat Rovira i Virgili, Human Nutrition Unit, Carrer Sant Llorenç, 21, 43201, Reus, Spain
- Institut ďInvestigació Sanitària Pere Virgili (IISPV), 43204, Reus, Spain
- University Hospital of Sant Joan de Reus, Nutrition Unit, 43201, Reus, Spain
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERObn), Institute of Health Carlos III, 28029, Madrid, Spain
| | - Nancy Babio
- Department of Biochemistry and Biotechonology, Universitat Rovira i Virgili, Human Nutrition Unit, Carrer Sant Llorenç, 21, 43201, Reus, Spain
- Institut ďInvestigació Sanitària Pere Virgili (IISPV), 43204, Reus, Spain
- University Hospital of Sant Joan de Reus, Nutrition Unit, 43201, Reus, Spain
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERObn), Institute of Health Carlos III, 28029, Madrid, Spain
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12
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Wang Z, Dong X, Song Q, Cui X, Shi Z, Zang J, Su J, Sun X. Jiangnan dietary pattern actively prevents muscle mass loss: Based on a cohort study. J Hum Nutr Diet 2021; 35:957-967. [PMID: 34231265 DOI: 10.1111/jhn.12934] [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: 05/29/2021] [Revised: 06/28/2021] [Accepted: 06/29/2021] [Indexed: 11/28/2022]
Abstract
BACKGROUND The proportion of sarcopenia in the elderly is very high, although muscle mass loss before sarcopenia covers a wider population. The present study aimed to analyse the effects of different dietary patterns on muscle mass. METHODS In both 2015 and 2018, using multilayer random sampling, the same participants were selected, and the same questionnaires and machines were used. RESULTS In total, 502 participants were selected. The >65-year-old group showed maximum muscle mass loss in males and females (-1.53 kg ± 4.42 and -1.14 kg ± 2.6 on average, respectively). The cumulative variance of four dietary patterns reached 52.28%. Logistical regression revealed significant differences between 'Jiangnan Dietary' groups: Q2 vs. Q1 [odds ratio (OR) = 0.356, 95% confidence interval (CI) = 0.202-0.629]; Q3 vs. Q1 (OR = 0.457, 95% CI = 0.262-0.797). Relative influence factors for muscle mass loss were age (>65 vs. <45, OR = 2.027, 95% CI = 1.117-3.680), physical activity (OR = 0.550, 95% CI = 0.315-0.960), income (high vs. low, OR = 0.413, 95% CI = 0.210 -0.810), sex (female vs. male, OR = 0.379, 95% CI = 0.235-0.519). CONCLUSIONS After 3 years of follow-up, participants' muscle mass declined significantly. The 'Jiangnan Dietary' pattern prevented muscle mass loss and is recommended to the wider population.
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Affiliation(s)
- Zhengyuan Wang
- Division of Health Risk Factors Monitoring and Control, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
| | - Xinyi Dong
- Division of Health Risk Factors Monitoring and Control, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
| | - Qi Song
- Division of Health Risk Factors Monitoring and Control, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
| | - Xueying Cui
- Division of Health Risk Factors Monitoring and Control, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
| | - Zehuan Shi
- Division of Health Risk Factors Monitoring and Control, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
| | - Jiajie Zang
- Division of Health Risk Factors Monitoring and Control, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
| | - Jin Su
- Division of Health Risk Factors Monitoring and Control, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
| | - Xiaodong Sun
- General Office, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
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