How does what we eat affect our health and longevity? It is a complex dynamic system

Summary: The study sheds new light on how natural differences in dietary patterns affect human aging, longevity, and overall health.

source: Columbia University

Answering a relatively brief question — how what we eat affects how we age — is inevitably complex, according to a new study in the Columbia Butler Center on Aging at Columbia University’s Mailman School of Public Health.

While most analyzes were concerned with the effect of a single nutrient on a single outcome, the traditional one-dimensional approach to understanding the effects of diet on health and aging no longer provides the full picture: a healthy diet should be considered based on the balance of groups of nutrients, rather than optimizing a series of nutrients one by one.

Until now, little was known about how the natural variation in dietary patterns in humans affects the aging process.

The results are published online in the journal BMC Biology.

said Alan Cohen, Ph.D., associate professor of environmental health sciences at Columbia Mailman School.

“This study therefore provides further support for the importance of looking beyond ‘one nutrient at a time’ as one size fits all answers to the age-old question of how to live a long, healthy life.”

Cohen also points out that the findings are also consistent with several studies that highlight the need for increased protein intake in older adults, in particular, to compensate for sarcopenia and decreased physical performance associated with aging.

Using multidimensional modeling techniques to test the effects of nutrient intake on physiological dysregulation in older adults, researchers have identified key patterns of specific nutrients associated with lower biological aging.

“Our approach provides a roadmap for future studies to explore the full complexity of the nutritional aging landscape,” noted Cohen, who is also affiliated with the Columbia Butler Center on Aging.

The researchers analyzed data from 1,560 older men and women, aged 67-84 years, randomly selected between November 2003 and June 2005 from the regions of Montreal, Laval, or Sherbrooke in Quebec, Canada, who were re-examined annually for 3 years and then They were followed. Four years to assess how nutrient intake is related to the aging process on a large scale.

Aging and age-related loss of homeostasis (physiological dysregulation) were quantified by incorporation of biomarkers in the blood. Diet Effects used the Engineering Framework of Nutrition, applied to macronutrients and 19 micronutrients/nutrient subcategories.

The researchers installed a series of eight models to explore different dietary predictors and adjusted for income, education level, age, physical activity, number of comorbidities, gender, and current smoking status.

Four general patterns are observed:

  • The optimal level of nutrient intake was dependent on the aging scale used. Higher protein intake improved/reduced some factors of aging, while higher carbohydrate levels improved/reduced others;
  • There have been cases where intermediate levels of nutrients performed well for many outcomes (i.e. arguing against just more/less is a better perspective);
  • There is a wide tolerance for patterns of nutrient intake that do not deviate much from norms (‘homogeneous plateaus’).
  • The optimal levels of one nutrient often depend on the levels of another (such as vitamin E and vitamin C). Simpler analytical methods are insufficient to capture such correlations.

The research team also developed an interactive tool To allow users to explore how different combinations of micronutrients affect different aspects of aging.

This shows fruits and vegetables
Using multidimensional modeling techniques to test the effects of nutrient intake on physiological dysregulation in older adults, researchers have identified key patterns of specific nutrients associated with lower biological aging. The image is in the public domain

The results of this study are consistent with previous experimental work in mice that showed that high-protein diets may accelerate aging early in life, but are beneficial at older ages.

“These results are not experimental and will need to be validated in other contexts. Specific findings, such as the prominence of the vitamin E and vitamin C combination, may not be replicated in other studies.

“But the qualitative finding that there are no simple answers to optimal nutrition is likely to hold: it has been evident in nearly all of our analyzes, by a variety of approaches, and is consistent with evolutionary principles and much previous work,” Cohen said. .

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Co-authors are: Alistair M. Senior, David Rubenheimer, and Stephen J. Simpson, University of Sydney; Véronique Legault and Francis B. Lavoie, University of Sherbrooke, Quebec, Canada; Nancy Press and Valerie Turcot, CIUSSS-de-l’Estrie-CHUS, Sherbrooke, Canada; University Institute of Montreal, Montreal, Canada, University of Sherbrooke, Sherbrooke, Canada; Berit Gaudreau, University of Montreal, Montreal, Canada; David G. Le Couteur, University of Sydney and the Institute on Aging and Alzheimer’s and ANZAC Research Institute, Concord Hospital, New South Wales, Australia.

Financing: The study was supported by the Australian Research Council (ARC DECRA: DE180101520), and Canadian Institutes of Health Research (CIHR) grants 153011 and 62842; In addition to grants from Fonds de recherche du Québec (FRQ) Scholarship # 2020-VICO-279753, Quebec Network for Research on Aging.

About this diet and aging research news

author: Stephanie Berger
source: Columbia University
Contact: Stephanie Berger – Columbia University
picture: The image is in the public domain

original search: open access.
Multidimensional associations between nutrient intake and healthy aging in humansBy Alan Cohen et al. BMC Biology


Summary

Multidimensional associations between nutrient intake and healthy aging in humans

background

Little is known about how the natural variation in people’s dietary patterns affects the aging process. To date, most analyzes of the problem have used a one-dimensional model, which is concerned with the effects of a single nutrient on a single outcome. Perhaps our ability to understand the problem is complicated by the fact that both nutrition and the physiology of aging are very complex and multidimensional, involving a large number of functional interactions. Here we apply the Multidimensional Engineering Framework of Nutrition to data on biological aging from 1,560 older adults followed over a four-year period to assess the extent to which nutrient intake is related to the aging process at scale.

consequences

Aging and age-related loss of homeostasis (physiological dysregulation) were quantified by incorporation of biomarkers in the blood. Diet effects were modeled using the Nutrition Engineering Framework, applied to macronutrients and 19 micronutrients/nutrient subcategories. We observed four broad patterns: (1) The optimal level of nutrient intake was dependent on the aging scale used. Higher protein intake improved/reduced some factors of aging, while higher carbohydrate levels improved/reduced others; (2) there were non-linear factors where average levels of nutrients perform well for many outcomes (i.e. arguing against a simple more/less perspective is a better one); (3) There is a wide tolerance for patterns of nutrient intake that do not deviate much from norms (‘homogeneous plateaus’). (4) The optimal levels of one nutrient often depend on the levels of another (eg vitamin E, vitamin C). Simpler linear/univariate analytical methods are insufficient to capture such correlations. We present an interactive tool for exploring outcomes in the high-dimensional food space.

conclusion

Using multidimensional modeling techniques to test the effects of nutrient intake on physiological dysregulation in a cohort of older adults, we identified key patterns of specific nutrients associated with lower biological aging. Our approach provides a roadmap for future studies to explore the full complexity of the nutritional aging landscape.

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