Does the Vegan Diet Extend Your Lifespan?
Thus, many people wonder whether alternative diets, such as the vegan diet, help people live longer, healthier lives. In fact, you may have heard claims that vegans have a longer lifespan than omnivores.
However, its effects on longevity are much more nuanced.
This article explains whether vegans live longer than non-vegans.
Some Vegans May Live Longer
Research examining the link between plant-based diets and longevity has produced mixed results.
One large review of vegans and vegetarians in the United Kingdom, Germany, the United States, and Japan suggests that they have a 9% lower risk of death from all causes, compared with omnivores.
Another study examined Seventh Day Adventists in North America. The Seventh Day Adventist diet is typically plant-based, rich in whole foods, and free of alcohol and caffeine — although some may incorporate small amounts of eggs, dairy, or meat.
The study suggested that vegetarians and vegans may benefit from a 12% lower risk of death, compared with people who eat meat.
When separated from the rest, vegans had a 15% lower risk of dying prematurely from all causes, indicating that a vegan diet may indeed help people live longer than those who adhere to vegetarian or omnivorous eating patterns.
However, other studies in vegetarians in the United Kingdom and Australia report that they're no more likely to live longer than non-vegetarians.
Thus, there's no definitive link between veganism and lifespan.
Furthermore, most studies group vegetarians and vegans together, making it difficult to determine the exact effects of each diet on a person's life expectancy. Therefore, more research is needed solely on vegan diets before strong conclusions can be made.
Some scientific reviews suggest that vegetarian and vegan diets may help people live longer, but these findings aren't universal. As such, more comprehensive studies are necessary.
Why Do Some Vegans Live Longer?
Researchers theorize that vegans who live longer than average tend to do so for two main reasons involving both diet and lifestyle.
Vegan Diets Are Often Rich in Nutritious Compounds
Veganism eliminates all animal-based foods, including meat, dairy, eggs, and products derived from them. This usually results in a diet that's rich in fruits, vegetables, whole grains, legumes, nuts, and seeds.
Research suggests that diets loaded with these plant foods may help people live longer. The same can be said about diets low in red and processed meats.
Moreover, vegan diets tend to pack plenty of fiber, plant protein, and antioxidants.
Diets rich in these nutrients are believed to safeguard against obesity, type 2 diabetes, cancer, and heart disease — which could promote increased life expectancy.
Vegans Tend to Have Healthier Lifestyles
As a group, vegans may be more likely to pursue a health-conscious lifestyle compared with the general population.
For instance, research shows that vegans may be less likely to smoke or drink alcohol. They also appear more likely to maintain a normal body mass index (BMI), exercise regularly, and avoid overly processed junk foods.
Experts believe that this increased health consciousness may help explain why some vegans live longer than non-vegans.
Vegan diets tend to be rich in nutrients that may protect against illnesses and boost your lifespan. Many people who follow this eating pattern also make lifestyle choices, such as exercising regularly and avoiding processed foods, that may aid longevity.
Not All Vegans Live Longer
It's important to remember that not all vegan diets are rich in nutrients. In fact, some vegans may rely heavily on sugary, processed foods — which could negatively affect longevity.
Notably, studies that rate plant-based diets based on their relative amounts of processed versus nutritious foods suggest that only robust, well-planned plant-based diets are linked to an extended lifespan and lower risk of disease.
A healthy vegan diet is typically defined as one that's rich in minimally processed plant foods, such as fruits, vegetables, whole grains, legumes, nuts, and seeds, with very few processed junk foods.
Meanwhile, a poorly planned vegan diet may rely heavily on sweets, processed items, and other foods that are technically vegan but very poor in nutrients.
For instance, one study claims that plant-based diets as a whole may lower your risk of dying from heart disease by 8%. However, nutritious plant-based diets lower this risk by 25% — while unhealthy ones increase it by 32%.
Another suggests that improving the quality of a plant-based diet over 12-years may reduce the likelihood of dying prematurely by 10%. Conversely, reducing its quality over the same period may result in a 12% higher risk of premature death.
This may explain why a recent review found that while vegetarians are more likely to live longer than the general population, their life expectancy is no higher than that of similarly health-conscious meat eaters.
However, few studies directly compare the effects of healthy or unhealthy vegan diets to healthy or unhealthy omnivorous ones. Overall, more research is needed.
SUMMARYPoorly planned vegan diets likely don't offer the same health benefits as nutritious versions of the diet. Nutrient-poor vegan diets may even lower your life expectancy.
The Bottom Line
Vegan diets are linked to numerous health benefits, including a lower risk of obesity, type 2 diabetes, certain cancers, and heart disease. Some evidence indicates that they may also help you live longer.
Yet, like most diets, vegan diets vary in quality. This may partly explain why vegans don't always outlive non-vegans.
If you're vegan and looking to maximize any longevity-promoting effects, replace processed foods in your diet with whole plant foods like fruits, vegetables, legumes, whole grains, nuts, and seeds.
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By Eric Tate and Christopher Emrich
Disasters stemming from hazards like floods, wildfires, and disease often garner attention because of their extreme conditions and heavy societal impacts. Although the nature of the damage may vary, major disasters are alike in that socially vulnerable populations often experience the worst repercussions. For example, we saw this following Hurricanes Katrina and Harvey, each of which generated widespread physical damage and outsized impacts to low-income and minority survivors.
Mapping Social Vulnerability<p>Figure 1a is a typical map of social vulnerability across the United States at the census tract level based on the Social Vulnerability Index (SoVI) algorithm of <a href="https://onlinelibrary.wiley.com/doi/abs/10.1111/1540-6237.8402002" target="_blank"><em>Cutter et al.</em></a> . Spatial representation of the index depicts high social vulnerability regionally in the Southwest, upper Great Plains, eastern Oklahoma, southern Texas, and southern Appalachia, among other places. With such a map, users can focus attention on select places and identify population characteristics associated with elevated vulnerabilities.</p>
Fig. 1. (a) Social vulnerability across the United States at the census tract scale is mapped here following the Social Vulnerability Index (SoVI). Red and pink hues indicate high social vulnerability. (b) This bivariate map depicts social vulnerability (blue hues) and annualized per capita hazard losses (pink hues) for U.S. counties from 2010 to 2019.<p>Many current indexes in the United States and abroad are direct or conceptual offshoots of SoVI, which has been widely replicated [e.g., <a href="https://link.springer.com/article/10.1007/s13753-016-0090-9" target="_blank"><em>de Loyola Hummell et al.</em></a>, 2016]. The U.S. Centers for Disease Control and Prevention (CDC) <a href="https://www.atsdr.cdc.gov/placeandhealth/svi/index.html" target="_blank">has also developed</a> a commonly used social vulnerability index intended to help local officials identify communities that may need support before, during, and after disasters.</p><p>The first modeling and mapping efforts, starting around the mid-2000s, largely focused on describing spatial distributions of social vulnerability at varying geographic scales. Over time, research in this area came to emphasize spatial comparisons between social vulnerability and physical hazards [<a href="https://doi.org/10.1007/s11069-009-9376-1" target="_blank"><em>Wood et al.</em></a>, 2010], modeling population dynamics following disasters [<a href="https://link.springer.com/article/10.1007%2Fs11111-008-0072-y" target="_blank" rel="noopener noreferrer"><em>Myers et al.</em></a>, 2008], and quantifying the robustness of social vulnerability measures [<a href="https://doi.org/10.1007/s11069-012-0152-2" target="_blank" rel="noopener noreferrer"><em>Tate</em></a>, 2012].</p><p>More recent work is beginning to dissolve barriers between social vulnerability and environmental justice scholarship [<a href="https://doi.org/10.2105/AJPH.2018.304846" target="_blank" rel="noopener noreferrer"><em>Chakraborty et al.</em></a>, 2019], which has traditionally focused on root causes of exposure to pollution hazards. Another prominent new research direction involves deeper interrogation of social vulnerability drivers in specific hazard contexts and disaster phases (e.g., before, during, after). Such work has revealed that interactions among drivers are important, but existing case studies are ill suited to guiding development of new indicators [<a href="https://doi.org/10.1016/j.ijdrr.2015.09.013" target="_blank" rel="noopener noreferrer"><em>Rufat et al.</em></a>, 2015].</p><p>Advances in geostatistical analyses have enabled researchers to characterize interactions more accurately among social vulnerability and hazard outcomes. Figure 1b depicts social vulnerability and annualized per capita hazard losses for U.S. counties from 2010 to 2019, facilitating visualization of the spatial coincidence of pre‑event susceptibilities and hazard impacts. Places ranked high in both dimensions may be priority locations for management interventions. Further, such analysis provides invaluable comparisons between places as well as information summarizing state and regional conditions.</p><p>In Figure 2, we take the analysis of interactions a step further, dividing counties into two categories: those experiencing annual per capita losses above or below the national average from 2010 to 2019. The differences among individual race, ethnicity, and poverty variables between the two county groups are small. But expressing race together with poverty (poverty attenuated by race) produces quite different results: Counties with high hazard losses have higher percentages of both impoverished Black populations and impoverished white populations than counties with low hazard losses. These county differences are most pronounced for impoverished Black populations.</p>
Fig. 2. Differences in population percentages between counties experiencing annual per capita losses above or below the national average from 2010 to 2019 for individual and compound social vulnerability indicators (race and poverty).<p>Our current work focuses on social vulnerability to floods using geostatistical modeling and mapping. The research directions are twofold. The first is to develop hazard-specific indicators of social vulnerability to aid in mitigation planning [<a href="https://doi.org/10.1007/s11069-020-04470-2" target="_blank" rel="noopener noreferrer"><em>Tate et al.</em></a>, 2021]. Because natural hazards differ in their innate characteristics (e.g., rate of onset, spatial extent), causal processes (e.g., urbanization, meteorology), and programmatic responses by government, manifestations of social vulnerability vary across hazards.</p><p>The second is to assess the degree to which socially vulnerable populations benefit from the leading disaster recovery programs [<a href="https://doi.org/10.1080/17477891.2019.1675578" target="_blank" rel="noopener noreferrer"><em>Emrich et al.</em></a>, 2020], such as the Federal Emergency Management Agency's (FEMA) <a href="https://www.fema.gov/individual-disaster-assistance" target="_blank" rel="noopener noreferrer">Individual Assistance</a> program and the U.S. Department of Housing and Urban Development's Community Development Block Grant (CDBG) <a href="https://www.hudexchange.info/programs/cdbg-dr/" target="_blank" rel="noopener noreferrer">Disaster Recovery</a> program. Both research directions posit social vulnerability indicators as potential measures of social equity.</p>
Social Vulnerability as a Measure of Equity<p>Given their focus on social marginalization and economic barriers, social vulnerability indicators are attracting growing scientific interest as measures of inequity resulting from disasters. Indeed, social vulnerability and inequity are related concepts. Social vulnerability research explores the differential susceptibilities and capacities of disaster-affected populations, whereas social equity analyses tend to focus on population disparities in the allocation of resources for hazard mitigation and disaster recovery. Interventions with an equity focus emphasize full and equal resource access for all people with unmet disaster needs.</p><p>Yet newer studies of inequity in disaster programs have documented troubling disparities in income, race, and home ownership among those who <a href="https://eos.org/articles/equity-concerns-raised-in-federal-flood-property-buyouts" target="_blank">participate in flood buyout programs</a>, are <a href="https://www.eenews.net/stories/1063477407" target="_blank" rel="noopener noreferrer">eligible for postdisaster loans</a>, receive short-term recovery assistance [<a href="https://doi.org/10.1016/j.ijdrr.2020.102010" target="_blank" rel="noopener noreferrer"><em>Drakes et al.</em></a>, 2021], and have <a href="https://www.texastribune.org/2020/08/25/texas-natural-disasters--mental-health/" target="_blank" rel="noopener noreferrer">access to mental health services</a>. For example, a recent analysis of federal flood buyouts found racial privilege to be infused at multiple program stages and geographic scales, resulting in resources that disproportionately benefit whiter and more urban counties and neighborhoods [<a href="https://doi.org/10.1177/2378023120905439" target="_blank" rel="noopener noreferrer"><em>Elliott et al.</em></a>, 2020].</p><p>Investments in disaster risk reduction are largely prioritized on the basis of hazard modeling, historical impacts, and economic risk. Social equity, meanwhile, has been far less integrated into the considerations of public agencies for hazard and disaster management. But this situation may be beginning to shift. Following the adage of "what gets measured gets managed," social equity metrics are increasingly being inserted into disaster management.</p><p>At the national level, FEMA has <a href="https://www.fema.gov/news-release/20200220/fema-releases-affordability-framework-national-flood-insurance-program" target="_blank">developed options</a> to increase the affordability of flood insurance [Federal Emergency Management Agency, 2018]. At the subnational scale, Puerto Rico has integrated social vulnerability into its CDBG Mitigation Action Plan, expanding its considerations of risk beyond only economic factors. At the local level, Harris County, Texas, has begun using social vulnerability indicators alongside traditional measures of flood risk to introduce equity into the prioritization of flood mitigation projects [<a href="https://www.hcfcd.org/Portals/62/Resilience/Bond-Program/Prioritization-Framework/final_prioritization-framework-report_20190827.pdf?ver=2019-09-19-092535-743" target="_blank" rel="noopener noreferrer"><em>Harris County Flood Control District</em></a>, 2019].</p><p>Unfortunately, many existing measures of disaster equity fall short. They may be unidimensional, using single indicators such as income in places where underlying vulnerability processes suggest that a multidimensional measure like racialized poverty (Figure 2) would be more valid. And criteria presumed to be objective and neutral for determining resource allocation, such as economic loss and cost-benefit ratios, prioritize asset value over social equity. For example, following the <a href="http://www.cedar-rapids.org/discover_cedar_rapids/flood_of_2008/2008_flood_facts.php" target="_blank" rel="noopener noreferrer">2008 flooding</a> in Cedar Rapids, Iowa, cost-benefit criteria supported new flood protections for the city's central business district on the east side of the Cedar River but not for vulnerable populations and workforce housing on the west side.</p><p>Furthermore, many equity measures are aspatial or ahistorical, even though the roots of marginalization may lie in systemic and spatially explicit processes that originated long ago like redlining and urban renewal. More research is thus needed to understand which measures are most suitable for which social equity analyses.</p>
Challenges for Disaster Equity Analysis<p>Across studies that quantify, map, and analyze social vulnerability to natural hazards, modelers have faced recurrent measurement challenges, many of which also apply in measuring disaster equity (Table 1). The first is clearly establishing the purpose of an equity analysis by defining characteristics such as the end user and intended use, the type of hazard, and the disaster stage (i.e., mitigation, response, or recovery). Analyses using generalized indicators like the CDC Social Vulnerability Index may be appropriate for identifying broad areas of concern, whereas more detailed analyses are ideal for high-stakes decisions about budget allocations and project prioritization.</p>
By Jessica Corbett
Sen. Bernie Sanders on Tuesday was the lone progressive to vote against Tom Vilsack reprising his role as secretary of agriculture, citing concerns that progressive advocacy groups have been raising since even before President Joe Biden officially nominated the former Obama administration appointee.