Most previous analyses have been more concerned with the effects of a single nutrient on a single outcome which is the conventional approach to understanding the effects of diet on health and aging. But this unidimensional approach does not provide the full picture as healthy diets need to be considered based on the balance of a collection of nutrients rather than optimizing nutrients one by one. Little is known about how normal variation in dietary patterns affects the aging process. This study set out to find out how better to answer that relatively concise but complex question.
“Our ability to understand the problem has been complicated by the fact that both nutrition and the physiology of ageing are highly complex and multidimensional, involving a high number of functional interactions,” said Alan Cohen, Ph.D., associate professor of environmental health sciences at Columbia Mailman School. “This study, therefore, provides further support to the importance of looking beyond ‘a single nutrient at a time’ as the one size fits all response to the age-old question of how to live a long and healthy life.”
Cohen also points out that these results are also in line with numerous studies suggesting the need for increased protein intake in older people, in particular, to offset sarcopenia and the decreased physical performance that is associated with aging. Multidimensional modeling techniques were used to examine the effects of nutrient intake on physiological dysregulation in older adults, which identified patterns of specific nutrients that are associated with minimal biological aging. “Our approach presents a roadmap for future studies to explore the full complexity of the nutrition-aging landscape,” observed Cohen, who is also affiliated with the Butler Columbia Aging Center.
For this study, data was analyzed from 1560 men and women between the ages of 67-84 years old who were selected at random in areas of Quebec, Canada who contributed data about their lifestyle, health, and diet to an ongoing study. Participants were re-examined annually for 3 years and followed for over four years to assess how on a large scale how nutrient intake associates with the aging process.
Aging and the age-related loss of homeostasis were quantified via the integration of blood markers, and the effects of diet used the geometric framework for nutrition apple to macronutrient and 19 micronutrient subclasses. A series of 8 models explored the different nutritional predictors, and the researchers adjusted for factors such as sex, smoking status, age, physical activity levels, income, education level, and a number of comorbidities.
According to the researchers, 4 broad patterns were observed: 1. Optimum level of nutrient intake was dependent on the aging metric use. Increased protein intake improved some aging parameters while increased carbohydrate intake improved others. 2. Intermediate levels of nutrients performed well for many outcomes. 3. A broad tolerance for nutrient intake was observed that does not deviate too much from homeostatic plateaus. 4. The optimum level of one nutrient often depends on levels of another, and the researchers suggest that a simpler analytical approach would not be able to capture such associations.
“These results are not experimental and will need to be validated in other contexts. Specific findings, such as the salience of the combination of vitamin E and vitamin C, may well not replicate in other studies. But the qualitative finding that there are no simple answers to optimal nutrition is likely to hold up: it was evident in nearly all our analyses, from a wide variety of approaches, and is consistent with evolutionary principles and much previous work,” said Cohen.
Additionally, the researchers also developed an interactive tool that allows the users to explore how different combinations of 19 micronutrient variables affect the different aspects of aging such as oxygen transport dysregulation, liver/kidney function dysregulation, immune system dysregulation, lipid dysregulation, global physiological dysregulation, micronutrient dysregulation, phenotypic age, and Klemera-Doubal biological age. There is an emphasis on the effects of 3-way interaction between micronutrients, and visualized outcomes are composite health measures based on common biomarkers.
