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Thomas A, Belsky D, Gu Y. Healthy Lifestyle Behaviors and Biological Aging in the U.S. National Health and Nutrition Examination Surveys 1999-2018. J Gerontol A Biol Sci Med Sci 2023; 78:1535-1542. [PMID: 36896965 PMCID: PMC10460553 DOI: 10.1093/gerona/glad082] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Indexed: 03/11/2023] Open
Abstract
People who have a balanced diet and engage in more physical activity live longer, healthier lives. This study aimed to test the hypothesis that these associations reflect a slowing of biological processes of aging. We analyzed data from 42 625 participants (aged 20-84 years, 51% female participants) from the National Health and Nutrition Examination Surveys (NHANES), 1999-2018. We calculated adherence to a Mediterranean diet (MeDi) and level of leisure time physical activity (LTPA) using standard methods. We measured biological aging by applying the PhenoAge algorithm, developed using clinical and mortality data from NHANES-III (1988-94), to clinical chemistries measured from a blood draw at the time of the survey. We tested the associations of diet and physical activity measures with biological aging, explored synergies between these health behaviors, and tested heterogeneity in their associations across strata of age, sex, and body mass index. Participants who adhered to the MeDi and who did more LTPA had younger biological ages compared with those who had less-healthy lifestyles (high vs low MeDi tertiles: β = 0.14 standard deviation [SD] [95% confidence interval {CI}: -0.18, -0.11]; high vs sedentary LTPA, β = 0.12 SD [-0.15, -0.09]), in models controlled for demographic and socioeconomic characteristics. Healthy diet and regular physical activity were independently associated with lower clinically defined biological aging, regardless of age, sex, and BMI category.
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Affiliation(s)
- Aline Thomas
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University, New York, New York, USA
| | - Daniel W Belsky
- Butler Columbia Aging Center, Columbia University Mailman School of Public Health, New York, New York, USA
- Department of Epidemiology, Joseph P. Mailman School of Public Health, Columbia University, New York, New York, USA
| | - Yian Gu
- Department of Epidemiology, Joseph P. Mailman School of Public Health, Columbia University, New York, New York, USA
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Gertrude H. Sergievsky Center, and Department of Neurology, Columbia University, New York, New York, USA
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Wang S, Li W, Li S, Tu H, Jia J, Zhao W, Xu A, Xu W, Tsai MK, Chu DTW, Wen CP, Wu X. Association between plant-based dietary pattern and biological aging trajectory in a large prospective cohort. BMC Med 2023; 21:310. [PMID: 37592257 PMCID: PMC10433678 DOI: 10.1186/s12916-023-02974-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Accepted: 07/06/2023] [Indexed: 08/19/2023] Open
Abstract
BACKGROUND Aging is a dynamic and heterogeneous process that may better be captured by trajectories of aging biomarkers. Biological age has been advocated as a better biomarker of aging than chronological age, and plant-based dietary patterns have been found to be linked to aging. However, the associations of biological age trajectories with mortality and plant-based dietary patterns remained unclear. METHODS Using group-based trajectory modeling approach, we identified distinctive aging trajectory groups among 12,784 participants based on a recently developed biological aging measure acquired at four-time points within an 8-year period. We then examined associations between aging trajectories and quintiles of plant-based dietary patterns assessed by overall plant-based diet index (PDI), healthful PDI (hPDI), and unhealthful PDI (uPDI) among 10,191 participants who had complete data on dietary intake, using multivariable multinomial logistics regression adjusting for sociodemographic and lifestyles factors. Cox proportional hazards regression models were applied to investigate the association between aging trajectories and all-cause mortality. RESULTS We identified three latent classes of accelerated aging trajectories: slow aging, medium-degree, and high-degree accelerated aging trajectories. Participants who had higher PDI or hPDI had lower odds of being in medium-degree (OR = 0.75, 95% CI: 0.65, 0.86 for PDI; OR = 0.73, 95% CI: 0.62, 0.85 for hPDI) or high-degree (OR = 0.63, 95% CI: 0.46, 0.86 for PDI; OR = 0.62, 95% CI: 0.44, 0.88 for hPDI) accelerated aging trajectories. Participants in the highest quintile of uPDI were more likely to be in medium-degree (OR = 1.72, 95% CI: 1.48, 1.99) or high-degree (OR = 1.70, 95% CI: 1.21, 2.38) accelerated aging trajectories. With a mean follow-up time of 8.40 years and 803 (6.28%) participants died by the end of follow-up, we found that participants in medium-degree (HR = 1.56, 95% CI: 1.29, 1.89) or high-degree (HR = 3.72, 95% CI: 2.73, 5.08) accelerated aging trajectory groups had higher risks of death than those in the slow aging trajectory. CONCLUSIONS We identified three distinctive aging trajectories in a large Asian cohort and found that adopting a plant-based dietary pattern, especially when rich in healthful plant foods, was associated with substantially lowered pace of aging.
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Affiliation(s)
- Sicong Wang
- Department of Big Data in Health Science School of Public Health, and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- Alibaba-Zhejiang University Joint Research Center of Future Digital Healthcare, Hangzhou, Zhejiang, China
| | - Wenyuan Li
- Department of Big Data in Health Science School of Public Health, and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Shu Li
- Department of Big Data in Health Science School of Public Health, and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Huakang Tu
- Department of Big Data in Health Science School of Public Health, and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Junlin Jia
- Department of Big Data in Health Science School of Public Health, and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Wenting Zhao
- Department of Big Data in Health Science School of Public Health, and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Andi Xu
- Department of Big Data in Health Science School of Public Health, and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Wenxin Xu
- Department of Big Data in Health Science School of Public Health, and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Min Kuang Tsai
- Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Taiwan
| | | | - Chi Pang Wen
- Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Taiwan.
- Graduate Institute of Biomedical Sciences, College of Medicine, China Medical University, Taichung, Taiwan.
- Department of Medical Research, China Medical University Hospital, Taichung, Taiwan.
| | - Xifeng Wu
- Department of Big Data in Health Science School of Public Health, and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
- National Institute for Data Science in Health and Medicine, Zhejiang University, Hangzhou, Zhejiang, China.
- Cancer Center, Zhejiang University, Hangzhou, Zhejiang, China.
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Meng N, Zhou Y, Zhang Q, Yu X, Li H, Liu Y, Liu M, Li Q. Using Inflammatory Biological Age To Evaluate the Preventing Aging Effect of a Polyphenol-Probiotic-Enhanced Dietary Pattern in Adults Aged 50 Years and Older. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2023; 71:6314-6325. [PMID: 37057839 DOI: 10.1021/acs.jafc.2c07241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
A high-compliance dietary intervention was conducted for 2 weeks in adults aged 50 years and older to investigate the preventing aging effects of a polyphenol-probiotic-enhanced diet (P-diet) by using inflammatory biological age (IBA). Following the P-diet, levels of interleukin-6 (IL-6), IL-10, and C-reactive protein were reduced. These effects were accompanied by a significant increase in the richness of Lactobacillus and Bifidobacterium and decrease in CAG_56, as well as an increase in butyrate and acetate and decrease in lysine, uracil, and valine. We optimized a model by a back propagation artificial neural network to evaluate the degree of aging, with an R2 of 0.68. After the P-diet intervention, IBA was younger than chronological age and the inflammatory aging potential (Δage) was observably reduced by 90.12%, with change in Δage having a direct negative association with Akkermansia. Overall, P-diet may alleviate chronic low-grade inflammation and thus prevent the procession of inflammatory aging.
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Affiliation(s)
- Ning Meng
- College of Light Industry and Food Engineering, Guangxi University, Nanning, Guangxi 530004, China
- Academy of National Food and Strategic Reserves Administration, Beijing 100037, China
| | - Yang Zhou
- Wangdingdi Hospital, Nankai District, Tianjin 300191, China
| | - Qinren Zhang
- College of Light Industry and Food Engineering, Guangxi University, Nanning, Guangxi 530004, China
| | - Xiaohan Yu
- College of Light Industry and Food Engineering, Guangxi University, Nanning, Guangxi 530004, China
| | - He Li
- College of Light Industry and Food Engineering, Guangxi University, Nanning, Guangxi 530004, China
| | - Yanxiang Liu
- Academy of National Food and Strategic Reserves Administration, Beijing 100037, China
| | - Ming Liu
- Academy of National Food and Strategic Reserves Administration, Beijing 100037, China
| | - Quanyang Li
- College of Light Industry and Food Engineering, Guangxi University, Nanning, Guangxi 530004, China
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Martínez CF, Esposito S, Di Castelnuovo A, Costanzo S, Ruggiero E, De Curtis A, Persichillo M, Hébert JR, Cerletti C, Donati MB, de Gaetano G, Iacoviello L, Gialluisi A, Bonaccio M. Association between the Inflammatory Potential of the Diet and Biological Aging: A Cross-Sectional Analysis of 4510 Adults from the Moli-Sani Study Cohort. Nutrients 2023; 15:nu15061503. [PMID: 36986232 PMCID: PMC10056325 DOI: 10.3390/nu15061503] [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: 02/15/2023] [Revised: 03/16/2023] [Accepted: 03/18/2023] [Indexed: 03/30/2023] Open
Abstract
Chronological age (CA) may not accurately reflect the health status of an individual. Rather, biological age (BA) or hypothetical underlying "functional" age has been proposed as a relevant indicator of healthy aging. Observational studies have found that decelerated biological aging or Δage (BA-CA) is associated with a lower risk of disease and mortality. In general, CA is associated with low-grade inflammation, a condition linked to the risk of the incidence of disease and overall cause-specific mortality, and is modulated by diet. To address the hypothesis that diet-related inflammation is associated with Δage, a cross-sectional analysis of data from a sub-cohort from the Moli-sani Study (2005-2010, Italy) was performed. The inflammatory potential of the diet was measured using the Energy-adjusted Dietary Inflammatory Index (E-DIITM) and a novel literature-based dietary inflammation score (DIS). A deep neural network approach based on circulating biomarkers was used to compute BA, and the resulting Δage was fit as the dependent variable. In 4510 participants (men 52.0%), the mean of CA (SD) was 55.6 y (±11.6), BA 54.8 y (±8.6), and Δage -0.77 (±7.7). In a multivariable-adjusted analysis, an increase in E-DIITM and DIS scores led to an increase in Δage (β = 0.22; 95%CI 0.05, 0.38; β = 0.27; 95%CI 0.10, 0.44, respectively). We found interaction for DIS by sex and for E-DIITM by BMI. In conclusion, a pro-inflammatory diet is associated with accelerated biological aging, which likely leads to an increased long-term risk of inflammation-related diseases and mortality.
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Affiliation(s)
- Claudia F Martínez
- Department of Epidemiology and Prevention, IRCCS Neuromed, Via dell'Elettronica, 86077 Pozzilli, Italy
- Population Health Research Center, National Institute of Public Health, Cuernavaca 62100, Mexico
| | - Simona Esposito
- Department of Epidemiology and Prevention, IRCCS Neuromed, Via dell'Elettronica, 86077 Pozzilli, Italy
| | | | - Simona Costanzo
- Department of Epidemiology and Prevention, IRCCS Neuromed, Via dell'Elettronica, 86077 Pozzilli, Italy
| | - Emilia Ruggiero
- Department of Epidemiology and Prevention, IRCCS Neuromed, Via dell'Elettronica, 86077 Pozzilli, Italy
| | - Amalia De Curtis
- Department of Epidemiology and Prevention, IRCCS Neuromed, Via dell'Elettronica, 86077 Pozzilli, Italy
| | - Mariarosaria Persichillo
- Department of Epidemiology and Prevention, IRCCS Neuromed, Via dell'Elettronica, 86077 Pozzilli, Italy
| | - James R Hébert
- Cancer Prevention and Control Program and Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC 29208, USA
- Department of Nutrition, Connecting Health Innovations LLC, Columbia, SC 29201, USA
| | - Chiara Cerletti
- Department of Epidemiology and Prevention, IRCCS Neuromed, Via dell'Elettronica, 86077 Pozzilli, Italy
| | - Maria Benedetta Donati
- Department of Epidemiology and Prevention, IRCCS Neuromed, Via dell'Elettronica, 86077 Pozzilli, Italy
| | - Giovanni de Gaetano
- Department of Epidemiology and Prevention, IRCCS Neuromed, Via dell'Elettronica, 86077 Pozzilli, Italy
| | - Licia Iacoviello
- Department of Epidemiology and Prevention, IRCCS Neuromed, Via dell'Elettronica, 86077 Pozzilli, Italy
- Department of Medicine and Surgery, Research Center in Epidemiology and Preventive Medicine (EPIMED), University of Insubria, 21100 Varese-Como, Italy
| | - Alessandro Gialluisi
- Department of Epidemiology and Prevention, IRCCS Neuromed, Via dell'Elettronica, 86077 Pozzilli, Italy
| | - Marialaura Bonaccio
- Department of Epidemiology and Prevention, IRCCS Neuromed, Via dell'Elettronica, 86077 Pozzilli, Italy
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Johnson AA, English BW, Shokhirev MN, Sinclair DA, Cuellar TL. Human age reversal: Fact or fiction? Aging Cell 2022; 21:e13664. [PMID: 35778957 PMCID: PMC9381899 DOI: 10.1111/acel.13664] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2022] [Revised: 05/23/2022] [Accepted: 06/13/2022] [Indexed: 12/19/2022] Open
Abstract
Although chronological age correlates with various age‐related diseases and conditions, it does not adequately reflect an individual's functional capacity, well‐being, or mortality risk. In contrast, biological age provides information about overall health and indicates how rapidly or slowly a person is aging. Estimates of biological age are thought to be provided by aging clocks, which are computational models (e.g., elastic net) that use a set of inputs (e.g., DNA methylation sites) to make a prediction. In the past decade, aging clock studies have shown that several age‐related diseases, social variables, and mental health conditions associate with an increase in predicted biological age relative to chronological age. This phenomenon of age acceleration is linked to a higher risk of premature mortality. More recent research has demonstrated that predicted biological age is sensitive to specific interventions. Human trials have reported that caloric restriction, a plant‐based diet, lifestyle changes involving exercise, a drug regime including metformin, and vitamin D3 supplementation are all capable of slowing down or reversing an aging clock. Non‐interventional studies have connected high‐quality sleep, physical activity, a healthy diet, and other factors to age deceleration. Specific molecules have been associated with the reduction or reversal of predicted biological age, such as the antihypertensive drug doxazosin or the metabolite alpha‐ketoglutarate. Although rigorous clinical trials are needed to validate these initial findings, existing data suggest that aging clocks are malleable in humans. Additional research is warranted to better understand these computational models and the clinical significance of lowering or reversing their outputs.
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Affiliation(s)
- Adiv A Johnson
- Longevity Sciences, Inc. (dba Tally Health), Greenwich, Connecticut, USA
| | - Bradley W English
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of Aging Research, Harvard Medical School, Boston, Massachusetts, USA
| | - Maxim N Shokhirev
- Longevity Sciences, Inc. (dba Tally Health), Greenwich, Connecticut, USA
| | - David A Sinclair
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of Aging Research, Harvard Medical School, Boston, Massachusetts, USA
| | - Trinna L Cuellar
- Longevity Sciences, Inc. (dba Tally Health), Greenwich, Connecticut, USA
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