Estimating impact of food choices on life expectancy: A modeling study
Authors: Jan-Magnus Økland
Kjell Arne Johansson
Lars T Fadnes
Øystein A Haaland
Journal: PLoS Medicine (2022)
Discipline: CLINICAL MEDICINE
Keywords: Nutritional research; decision support model; life expectancy; diet; fruits
Affiliations: Department of Global Public Health and Primary Care, University of Bergen, Norway.

Abstract:  Background: Interpreting and utilizing the findings of nutritional research can be challenging to clinicians, policy makers, and even researchers. To make better decisions about diet, innovative methods that integrate best evidence are needed. We have developed a decision support model that predicts how dietary choices affect life expectancy (LE). Methods and findings: Based on meta-analyses and data from the Global Burden of Disease study (2019), we used life table methodology to estimate how LE changes with sustained changes in the intake of fruits, vegetables, whole grains, refined grains, nuts, legumes, fish, eggs, milk/dairy, red meat, processed meat, and sugar-sweetened beverages. We present estimates (with 95% uncertainty intervals [95% UIs]) for an optimized diet and a feasibility approach diet. An optimal diet had substantially higher intake than a typical diet of whole grains, legumes, fish, fruits, vegetables, and included a handful of nuts, while reducing red and processed meats, sugar-sweetened beverages, and refined grains. A feasibility approach diet was a midpoint between an optimal and a typical Western diet. A sustained change from a typical Western diet to the optimal diet from age 20 years would increase LE by more than a decade for women from the United States (10.7 [95% UI 8.4 to 12.3] years) and men (13.0 [95% UI 9.4 to 14.3] years). The largest gains would be made by eating more legumes (females: 2.2 [95% UI 1.1 to 3.4]; males: 2.5 [95% UI 1.1 to 3.9]), whole grains (females: 2.0 [95% UI 1.3 to 2.7]; males: 2.3 [95% UI 1.6 to 3.0]), and nuts (females: 1.7 [95% UI 1.5 to 2.0]; males: 2.0 [95% UI 1.7 to 2.3]), and less red meat (females: 1.6 [95% UI 1.5 to 1.8]; males: 1.9 [95% UI 1.7 to 2.1]) and processed meat (females: 1.6 [95% UI 1.5 to 1.8]; males: 1.9 [95% UI 1.7 to 2.1]). Changing from a typical diet to the optimized diet at age 60 years would increase LE by 8.0 (95% UI 6.2 to 9.3) years for women and 8.8 (95% UI 6.8 to 10.0) years for men, and 80-year-olds would gain 3.4 years (95% UI females: 2.6 to 3.8/males: 2.7 to 3.9). Change from typical to feasibility approach diet would increase LE by 6.2 (95% UI 3.5 to 8.1) years for 20-year-old women from the United States and 7.3 (95% UI 4.7 to 9.5) years for men. Using NutriGrade, the overall quality of evidence was assessed as moderate. The methodology provides population estimates under given assumptions and is not meant as individualized forecasting, with study limitations that include uncertainty for time to achieve full effects, the effect of eggs, white meat, and oils, individual variation in protective and risk factors, uncertainties for future development of medical treatments; and changes in lifestyle. Conclusions: A sustained dietary change may give substantial health gains for people of all ages both for optimized and feasible changes. Gains are predicted to be larger the earlier the dietary changes are initiated in life. The Food4HealthyLife calculator that we provide online could be useful for clinicians, policy makers, and laypeople to understand the health impact of dietary choices. 

Retracted: No

PubPeer comments:
 This comment was posted as a preprint and as a comment on the published article. Authors: **Vegard Lysne, Thomas Olsen, Theogene Habumugisha, Ingunn M.S. Engebretsen, Jutta Dierkes** The modeling study by Fadnes et al just published in PLOS Medicine has amassed considerable news and social media attention for its claim that an optimized diet could lead to as much as 13 additional years of life expectancy (1). At the time of writing, the study has been viewed more than 120,000 times and generated 247 generally favorable news stories including major news outlets such as CNN and The Telegraph. Although the research effort is ambitious and admirable, the messages that have reached the general public are grossly oversimplified from a nutritional point of view and we have substantial reservations about the methodological approach, interpretations, and conclusions from this study. The study additively combines effect estimates from published meta-analyses on diet-disease associations for individual foods and food groups to estimate total life-years gained by sustained dietary changes. Although we agree that transitioning to a healthy diet will result in healthy life years gains, we consider the estimates reported in the paper and thereafter in news headlines as implausible for several reasons. Firstly, any changes in energy intake are neglected. This is one of the most important components of dietary exposure and a crucial determinant of health both in under- and overnutrition. Secondly, the effects of changing the intake of individual foods are treated separately and independently, practically ignoring food substitution effects which is a key concept in nutrition research (2) Whenever the intake of one food changes, this is inevitably followed by changes in the intake of other foods and in most cases total energy intake. Thus, health effects must always be interpreted in light of which food is replaced. Thirdly, the individual effect estimates are highly overlapping and influenced by both socioeconomic status (SES) and health consciousness, which are major determinants of longevity. When additively combined, this inevitably causes the model to overestimate the total effect. We also question the validity of the dietary intake estimates used to calculate the expected effect of specific dietary changes. Food frequency questionnaires (FFQ) are the dietary tool most used for the underlying data. FFQs are mainly used to rank individuals according to dietary exposure, and thus well suited for relative comparisons across different intake levels. However, estimates of absolute intakes should be interpreted with caution due to the presence of systematic measurement error. The model developed by Fadnes et al gives the impression of being able to predict the effect of very specific food intake levels, and we are concerned that this could be interpreted literally by the end-user. Further, we cannot reasonably assume that the health effects of any food are homogeneous across all population groups, i.e. there is no such thing as u2018one size fits allu2019 in nutrition. Among other things, the model does not adequately consider acceptability and the situation in low- and middle-income countries (LMICs) or the growing concern of undernutrition among vulnerable subgroups of the population. A fitting example for the issue of LMICs is the PURE study, where diet-disease associations oppose what has been typically observed in Western populations (3) However, baseline nutrition status and food intake in LMICs differ from what is observed in Western affluent populations, and different foods are associated with higher SES. In contrast to the EAT-Lancet commissionu2019s healthy diet from sustainable food systems (4), the optimal diet described in this paper eliminates red meat and drastically increases legumes and fish above and beyond what is practically feasible or sustainable. Indeed, eliminating intakes of entire food groups could do more harm than good for specific subgroups. For instance, lowering red meat intake would most likely be beneficial for the majority (5,6). At the same time, as a considerable source of protein, energy, and many micronutrients, the effect is likely not the same in populations at risk of undernutrition, such as the elderly, as we previously suggested (7). As emphasized by EAT-Lancet, moderate meat consumption can provide adequate nutrients4, and it can be obtained from sustainably produced livestock (8). Healthy skepticism has been advised when interpreting observational research on preventive interventions, especially when results appear surprisingly large (9). Unfortunately, we think that the results from Fadnes et al join the ranks of implausible effects. The authors clearly state, and we agree, that the model is not meant for individualized forecasting. Nonetheless, they go on to conclude that clinicians, policymakers, and laypeople could use the calculator to understand the effect of dietary choices. Although we consider the estimated gains in life expectancy as exaggerated, we agree that dietary changes in the general direction described in the paper would benefit the majority in the Western world and would imply reduced meat intake and increased vegetable, legumes, and fish intakes. This includes huge changes for the food systems and questions the sustainability of fish stocks (4). 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