Top 10 Biggest Myths in ‘Alternative’ Nutrition
Even with evidence to support them, mainstream and alternative practitioners often disagree on best practices.
However, some people hold beliefs about nutrition that have no scientific support.
This article looks at some of the myths that people sometimes share in the field of alternative nutrition.
1. Sugar: Eight Times More Addictive Than Cocaine?
Sugar occurs naturally in many foods, especially fruits and vegetables. However, it's also a popular additive.
There's plenty of evidence that adding too much sugar to food is harmful. Scientists have linked it with obesity, insulin resistance, increases in belly fat and liver fat, and diseases such as type 2 diabetes and heart disease.
However, avoiding added sugar can be difficult. One reason is that manufacturers add it to many premade foods, including savory sauces and fast foods.
In addition, some people experience cravings for foods that are high in sugar.
This has led some experts to believe that sugar and the foods that contain it have addictive properties.
There's evidence to support this in both animals and humans. Sugar can activate the same areas in the brain as recreational drugs, and it can cause similar behavioral symptoms.
Some go as far as to claim that sugar is 8 times more addictive than cocaine.
This claim stems from a study that found that rats preferred water sweetened with sugar or saccharin over intravenous cocaine.
It was a striking result but didn't prove that sugar has an eightfold addictive lure for humans, compared to cocaine.
Sugar can trigger health problems, and it may be addictive. However, it's unlikely to be more addictive than cocaine.
Sugar can be an unhealthy addition to food, and it may be addictive. However, it's unlikely to be 8 times as addictive as cocaine.
2. Calories Don't Matter at All
Some people think that calories are all that matter for weight loss.
Others say that you can lose weight no matter how many calories you eat, as long as you choose the right foods. They consider calories irrelevant.
The truth is somewhere in between.
Eating certain foods can help support weight loss, for example, by:
- boosting metabolism, which increases the number of calories you use
- reducing appetite, which decreases the number of calories you consume
Many people can lose weight without counting calories.
However, it's a fact that if you lose weight, more calories are leaving your body than entering it.
This doesn't mean that you need to count calories to lose weight.
Changing your diet so that weight loss happens on "autopilot" can be just as effective, if not better.
Some people believe that calories make no difference to weight loss or gain. Calorie counting isn't always necessary, but calories still count.
3. Cooking With Olive Oil is a Bad Idea
Extra virgin olive oil is one of the healthiest fats available.
However, many people believe it's unhealthy to use it for cooking.
Fats and antioxidants are sensitive to heat. When you apply heat, harmful compounds may form.
The polyunsaturated fat content of olive oil is only 10–11%. This is low, compared with most other plant oils.
Indeed, studies have shown that olive oil maintains some of its healthful properties, even at high heat.
Although there may be a loss of antioxidants, vitamin E, and flavor, olive oil retains most of its nutritional properties when heated.
Olive oil is a healthy choice of oil, whether raw or in cooking.
Olive oil can be a suitable choice for cooking. Studies show that it can withstand cooking temperatures, even for long periods of time.
4. Microwaves Damage Your Food and Emit Harmful Radiation
Heating food in a microwave oven is fast and highly convenient, but some people believe this comes at a cost.
They claim that microwaves produce harmful radiation and can damage the nutrients in food. However, there doesn't appear to be any published evidence to support this.
Microwave ovens use radiation, but their design prevents this from escaping.
In fact, research suggests that microwave cooking may be better for preserving nutrients than other cooking methods, such as boiling or frying.
There's no scientific evidence that microwave cooking is harmful.
No published studies show that microwave ovens are harmful. On the contrary, some research suggests they may help preserve nutrients that other cooking methods destroy.
5. Blood Cholesterol Doesn't Matter
Nutritionists often disagree on the effect of saturated fats and dietary cholesterol.
Mainstream organizations, such as the American Heart Association (AHA) recommend limiting the intake of saturated fats to 5–6% of calories, while the 2015–2020 Dietary Guidelines for Americans recommend a maximum of 10% for the general population.
Meanwhile, some evidence suggests that consuming foods that are high in cholesterol and saturated fats may not increase the risk of heart disease.
The Dietary Guidelines no longer contain advice on limiting cholesterol intake to 300 mg a day in 2015. However, they still recommend eating as little dietary cholesterol as possible while following a healthy diet.
However, some people have misunderstood this and believe that blood cholesterol levels are also unimportant.
Having high levels of cholesterol in your blood can increase your cardiovascular disease and other health conditions. You shouldn't disregard them.
Following a healthful lifestyle — including a diet that's rich in fresh fruits and vegetables and low in processed foods, fat, and sugar — can help you maintain suitable cholesterol levels.
Cholesterol and saturated fat in foods may be harmless, but cholesterol levels in the bloodstream can affect your heart disease risk.
6. Store-Bought Coffee Contains High Levels of Mycotoxins
Mycotoxins are toxins that come from molds.
They're present in many popular foods.
There's a myth that most coffee contains harmful levels of mycotoxins.
However, this is unlikely to be true. There are strict regulations controlling mycotoxin levels in foods. If a crop exceeds the safety limit, the producer must discard it.
Studies show that if you drink 4 cups of coffee a day, you would consume only 2% of the mycotoxin intake that's deemed safe. These levels are well within the safety margin.
There's no need to fear coffee due to mycotoxins.
Mycotoxins are everywhere, but the levels in coffee are well within safety limits.
7. Alkaline Foods Are Healthy, Acidic Foods Cause Disease
Some people follow an alkaline diet.
- Foods have either an acidic or an alkaline effect on the body.
- Acidic foods lower the pH value of the blood, making it more acidic.
- Cancer cells only grow in an acidic environment.
However, research doesn't support this view. The truth is, the body regulates the blood's pH value, regardless of diet. It only changes significantly if a person has severe poisoning or a health condition such as chronic kidney disease.
A person's blood is slightly alkaline by default, and cancer can also grow in an alkaline environment.
The alkaline diet may be healthy, but that's because it's based on healthy, whole foods. Whether these foods are "alkaline" or "acidic" is unlikely to have an effect.
Foods cannot change the pH value (acidity) of the blood in healthy people. There's no convincing evidence to support the alkaline diet.
8. Eating Dairy is Bad for Your Bones
Another myth states that dairy causes osteoporosis. This is an extension of the alkaline diet myth.
Supporters claim that dairy protein makes the blood acidic and the body takes calcium out of your bones to neutralize the acidity.
In reality, there are several properties in dairy foods that support bone health.
They're a good source of calcium and phosphorus, the main building blocks of bones. They also contain vitamin K-2, which may contribute to bone formation.
They're also a good source of protein, which is useful for bone health, according to research.
Studies indicate that dairy products can improve bone health in all age groups by increasing bone density and lowering the risk of fractures.
Many of these studies are controlled trials in humans.
While dairy isn't essential for bone health, it can be highly beneficial.
Some people claim that dairy products can harm bone health, but most studies show the opposite.
9. Carbs Are Inherently Harmful
Low-carb diets have numerous benefits.
Studies show they can help people lose weight and improve various health markers, especially for metabolic syndrome and type 2 diabetes.
If lowering carbs can help treat certain health problems, some people believe carbs must have caused the problem in the first place.
As a result, many low-carbers have come to demonize all high carb foods, including those that offer a range of benefits, such as potatoes, apples, and carrots.
It's true that refined carbs, including added sugars and refined grains, can contribute to weight gain and metabolic disease.
However, this is not true for whole carbohydrate sources.
When metabolic problems already exist — such as with obesity and type 2 diabetes — a low carb diet can help.
However, that doesn't mean that carbs caused these health problems.
Many people remain in excellent health while eating plenty of unprocessed high carbohydrate foods, such as whole grains.
A low carb diet is a healthy option for some people, but it's not necessary or suitable for everyone.
Low carb diets can help some people, but this doesn't mean that carbs are unhealthy, especially those that are whole and unprocessed.
10. Agave Nectar is a Healthy Sweetener
The health food market has expanded rapidly in recent years, but not all of its products are healthy.
One example is the sweetener agave nectar.
Added sugars can cause health problems, and one reason is their high fructose content.
The liver can only metabolize certain amounts of fructose. If there's too much fructose, the liver starts turning it into fat.
Agave nectar has a higher fructose content than both regular sugar and high fructose corn syrup.
This may make agave nectar one of the least healthy sweeteners on the market.
Agave nectar is high in fructose, which can be difficult for the liver to metabolize. It is better to avoid sweeteners and added sugar where possible.
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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.