3 Omega-3 Fatty Acids That Should Be Part of Your Diet
By Freydis Hjalmarsdottir
Omega-3 fatty acids are essential fats that have numerous benefits for health. However, not all omega-3 fatty acids are created equal—in fact, there are 11 different types, and some are better for you than others.
The three most important ones are ALA, EPA and DHA. ALA is mostly found in plants, while EPA and DHA are mostly found in animal foods like fatty fish.
Photo credit: Shutterstock
Omega-3 Fatty Acids: A Recap
Like all fatty acids, omega-3s are chains of carbon, hydrogen and oxygen atoms.
Omega-3 fatty acids are polyunsaturated, meaning they have two or more double bonds (poly = many) in their chemical structure. Just like the omega-6s, omega-3 fatty acids cannot be made by the body and we must get them from the diet. This is why they are termed essential fatty acids.
Omega-3 fatty acids are not simply stored and used for energy. They have important roles in all sorts of bodily processes, including inflammation, heart health and brain function. Being deficient in omega-3s is associated with lower intelligence, depression, heart disease, arthritis, cancer and many other health problems (1, 2).
1. ALA (Alpha-Linolenic Acid)
ALA is short for alpha-linolenic acid. This is the most common omega-3 fatty acid in the diet. It is 18 carbons long with three double bonds.
ALA is mostly found in plant foods and needs to be converted into the EPA or DHA before it can be utilized by the human body.
When ALA is not converted to EPA or DHA, it remains inactive and is simply stored or used as energy, like other fats. Some observational studies have found an association between a diet rich in ALA and a reduced risk of heart disease deaths, while others have found an increased risk of prostate cancer (7).
This increase in prostate cancer risk was not associated with the other main omega-3 types, EPA and DHA, which actually had a protective effect (8).
ALA is found in many plant foods, including kale, spinach, purslane, soybeans,walnuts and many seeds such as chia, flax and hemp seeds. ALA is also found in some animal fats. Some seed oils, such as flaxseed oil and rapeseed (canola) oil are also high in ALA.
Bottom Line: ALA is short for alpha-linolenic acid. It is mostly found in plant foods and needs to be converted into EPA or DHA in order to become active in the human body.
2. EPA (Eicosapentaenoic Acid)
EPA is short for eicosapentaenoic acid. It is 20 carbons long, with 5 double bonds.
Its main function is to form signaling molecules called eicosanoids, which play numerous physiological roles.
Eicosanoids made from omega-3s reduce inflammation, while those made from omega-6s tend to increase inflammation (9).
For this reason, a diet high in EPA may reduce inflammation in the body. Chronic, low-level inflammation is known to drive several common diseases (10).
One study also found that EPA reduced the number of hot flashes experienced by menopausal women (13).
Both EPA and DHA are mostly found in seafood, including fatty fish and algae. For this reason, they are often called marine omega-3s.
EPA concentrations are highest in herring, salmon, eel, shrimp and sturgeon. Grass-fed animal products, such as dairy and meats, also contain some EPA.
3. DHA (Docosahexaenoic Acid)
DHA is short for docosahexaenoic acid. It is 22 carbons long, with 6 double bonds.
DHA is an important structural component of skin and the retina in the eye (14).
Fortifying baby formula with DHA leads to improved vision in infants (15).
DHA is absolutely vital for brain development and function in childhood, as well as brain function in adults.
Early-life DHA deficiency is associated with problems later on, such as learning disabilities, ADHD, aggressive hostility and several other disorders (16).
A decrease in DHA during aging is also associated with impaired brain function and the onset of Alzheimer's disease (17).
DHA is also reported to have positive effects on diseases such as arthritis, high blood pressure, type 2 diabetes and some cancers (18).
The role of DHA in heart disease is also well established. It can reduce blood triglycerides and may lead to fewer harmful LDL particles (19).
As mentioned before, DHA is found in high amounts in seafood, including fatty fish and algae. Grass-fed animal products also contain some DHA.
Bottom Line: DHA is short for docosahexaenoic acid. It is a long-chain omega-3 fatty acid that is very important for brain development. It may also help protect against heart disease, cancer and other health problems.
Conversion Process: From ALA to EPA to DHA
ALA, the most common omega-3 fat, needs to be converted into EPA or DHA to become “active" (3).
Furthermore, the conversions are dependent on adequate levels of other nutrients, such as vitamins B6 and B7, copper, calcium, magnesium, zinc and iron. Many of these are lacking in the modern diet, especially among vegetarians (23).
The low conversion rate is also because omega-6 fatty acids compete for the same enzymes needed for the conversion process. Therefore, the high amount of omega-6 in the modern diet can reduce the conversion of ALA to EPA and DHA (5, 24).
8 Other Omega-3 Fatty Acids
ALA, EPA and DHA are the most abundant omega-3 fatty acids in the diet.
However, at least 8 other omega-3 fatty acids have been discovered:
- Hexadecatrienoic acid (HTA).
- Stearidonic acid (SDA).
- Eicosatrienoic acid (ETE).
- Eicosatetraenoic acid (ETA).
- Heneicosapentaenoic acid (HPA).
- Docosapentaenoic acid (DPA).
- Tetracosapentaenoic acid.
- Tetracosahexaenoic acid.
These fatty acids are found in some foods, but are not considered essential. However, some of of them do have biological effects.
Bottom Line: At least 8 other omega-3 fatty acids have been discovered. They are found in some foods and can have biological effects.
Which Omega-3 Fatty Acid is Best?
The most important omega-3 fatty acids are EPA and DHA.
If you don't eat a lot of these foods, then omega-3 supplements can be useful.
This article was reposted from our media associate Authority Nutrition.
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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>
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