Eggcellent News Against Dementia?
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It’s that time of the week again… We hope all our readers have had a great and healthy week! Here are some selections from health news from around the world:
Moderation remains key
Eggs have come under the spotlight for their protective potential against dementia, largely due to their content of omega-3 fatty acids, choline, and other nutrients.
Nevertheless, the study had some limitations (including not measuring the quantity of eggs consumed, just the frequency), and while eating eggs daily showed the lowest rates of dementia, not eating them at all did not significantly alter the risk.
Eating more than 2 eggs per day is still not recommended, however, for reasons of increasing the risk of other health issues, such as heart disease.
Read in full: Could eating eggs prevent dementia?
Related: Eggs: Nutritional Powerhouse or Heart-Health Timebomb?
More than suitable
It’s common for a lot of things to come with the warning “not suitable for those who are pregnant or nursing”, with such frequency that it can be hard to know what one can safely do/take while pregnant or nursing.
In the case of COVID vaccines, though, nearly 90% of babies who had to be hospitalized with COVID-19 had mothers who didn’t get the vaccine while they were pregnant.
And as for how common that is: babies too young to be vaccinated (so, under 6 months) had the highest covid hospitalization rate of any age group except people over 75.
Read in full: Here’s why getting a covid shot during pregnancy is important
Related: The Truth About Vaccines
Positive dieting
Adding things into one’s diet is a lot more fun than taking things out, is generally easier to sustain, and (as a general rule of thumb; there are exceptions of course) give the greatest differences in health outcomes.
This is perhaps most true of beans and pulses, which add many valuable vitamins, minerals, protein, and perhaps most importantly of all (single biggest factor in reducing heart disease risk), fiber.
Read in full: Adding beans and pulses can lead to improved shortfall nutrient intakes and a higher diet quality in American adults
Related: Intuitive Eating Might Not Be What You Think
Clearing out disordered thinking
Hoarding is largely driven by fear of loss, and this radical therapy tackles that at the root, by such means as rehearsing alternative outcomes of discarding through imagery rescripting, and examining the barriers to throwing things away—to break down those barriers one at a time.
Read in full: Hoarding disorder: sensory CBT treatment strategy shows promise
Related: When You Know What You “Should” Do (But Knowing Isn’t The Problem)
Superfluous
Fluoridated water may not be as helpful for the teeth as it used to be prior to about 1975. Not because it became any less effective per se, but because of the modern prevalence of fluoride-containing toothpastes, mouthwashes, etc rendering it redundant in more recent decades.
Read in full: Dental health benefits of fluoride in water may have declined, study finds
Related: Water Fluoridation, Atheroma, & More
Off-label?
With rising costs of living including rising healthcare costs, and increasing barriers to accessing in-person healthcare, it’s little wonder that many are turning to the gray market online to get their medications.
These websites typically use legal loopholes to sell prescription drugs to the public, by employing morally flexible doctors who are content to expediently rubber-stamp prescriptions upon request, on the basis of the patient having filled out a web form and checked boxes for their symptoms (and of course also having waived all rights of complaint or legal recourse).
However, some less scrupulous sorts are exploiting this market, to sell outright fake medications, using a setup that looks like a “legitimate” gray market website. Caveat emptor indeed.
Read in full: CDC warns of fake drug dangers from online pharmacies
Related: Are You Taking PIMs? Getting Off The Overmedication Train
A rising threat
In 2021 (we promise the paper was published only a few days ago!), the leading causes of death were:
- COVID-19
- Heart disease
- Stroke
…which latter represented a rising threat, likely in part due to the increase in the aging population.
Read in full: Stroke remains a leading cause of death globally, with increased risk linked to lifestyle factors
Related: 6 Signs Of Stroke (One Month In Advance)
Take care!
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How Science News Outlets Can Lie To You (Yes, Even If They Cite Studies!)
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Each Monday, we’re going to be bringing you cutting-edge research reviews to not only make your health and productivity crazy simple, but also, constantly up-to-date.
But today, in this special edition, we want to lay out plain and simple how to see through a lot of the tricks used not just by popular news outlets, but even sometimes the research publications themselves.
That way, when we give you health-related science news, you won’t have to take our word for it, because you’ll be able to see whether the studies we cite really support the claims we make.
Of course, we’ll always give you the best, most honest information we have… But the point is that you shouldn’t have to trust us! So, buckle in for today’s special edition, and never have to blindly believe sci-hub (or Snopes!) again.
The above now-famous Tumblr post that became a meme is a popular and obvious example of how statistics can be misleading, either by error or by deliberate spin.
But what sort of mistakes and misrepresentations are we most likely to find in real research?
Spin Bias
Perhaps most common in popular media reporting of science, the Spin Bias hinges on the fact that most people perceive numbers in a very “fuzzy logic” sort of way. Do you?
Try this:
- A million seconds is 11.5 days
- A billion seconds is not weeks, but 13.2 months!
…just kidding, it’s actually nearly thirty-two years.
Did the months figure seem reasonable to you, though? If so, this is the same kind of “human brains don’t do large numbers” problem that occurs when looking at statistics.
Let’s have a look at reporting on statistically unlikely side effects for vaccines, as an example:
- “966 people in the US died after receiving this vaccine!” (So many! So risky!)
- “Fewer than 3 people per million died after receiving this vaccine!” (Hmm, I wonder if it is worth it?)
- “Half of unvaccinated people with this disease die of it” (Oh)
How to check for this: ask yourself “is what’s being described as very common really very common?”. To keep with the spiders theme, there are many (usually outright made-up) stats thrown around on social media about how near the nearest spider is at any given time. Apply this kind of thinking to medical conditions.. If something affects only 1% of the population (So few! What a tiny number!), how far would you have to go to find someone with that condition? The end of your street, perhaps?
Selection/Sampling Bias
Diabetes disproportionately affects black people, but diabetes research disproportionately focuses on white people with diabetes. There are many possible reasons for this, the most obvious being systemic/institutional racism. For example, advertisements for clinical trial volunteer opportunities might appear more frequently amongst a convenient, nearby, mostly-white student body. The selection bias, therefore, made the study much less reliable.
Alternatively: a researcher is conducting a study on depression, and advertises for research subjects. He struggles to get a large enough sample size, because depressed people are less likely to respond, but eventually gets enough. Little does he know, even the most depressed of his subjects are relatively happy and healthy compared with the silent majority of depressed people who didn’t respond.
See This And Many More Educational Cartoons At Sketchplanations.com!
How to check for this: Does the “method” section of the scientific article describe how they took pains to make sure their sample was representative of the relevant population, and how did they decide what the relevant population was?
Publication Bias
Scientific publications will tend to prioritise statistical significance. Which seems great, right? We want statistically significant studies… don’t we?
We do, but: usually, in science, we consider something “statistically significant” when it hits the magical marker of p=0.05 (in other words, the probability of getting that result is 1/20, and the results are reliably coming back on the right side of that marker).
However, this can result in the clinic stopping testing once p=0.05 is reached, because they want to have their paper published. (“Yay, we’ve reached out magical marker and now our paper will be published”)
So, you can think of publication bias as the tendency for researchers to publish ‘positive’ results.
If it weren’t for publication bias, we would have a lot more studies that say “we tested this, and here are our results, which didn’t help answer our question at all”—which would be bad for the publication, but good for science, because data is data.
To put it in non-numerical terms: this is the same misrepresentation as the technically true phrase “when I misplace something, it’s always in the last place I look for it”—obviously it is, because that’s when you stop looking.
There’s not a good way to check for this, but be sure to check out sample sizes and see that they’re reassuringly large.
Reporting/Detection/Survivorship Bias
There’s a famous example of the rise in “popularity” of left-handedness. Whilst Americans born in ~1910 had a bit under a 3.5% chance of being left handed, those born in ~1950 had a bit under a 12% change.
Why did left-handedness become so much more prevalent all of a sudden, and then plateau at 12%?
Simple, that’s when schools stopped forcing left-handed children to use their right hands instead.
In a similar fashion, countries have generally found that homosexuality became a lot more common once decriminalized. Of course the real incidence almost certainly did not change—it just became more visible to research.
So, these biases are caused when the method of data collection and/or measurement leads to a systematic error in results.
How to check for this: you’ll need to think this through logically, on a case by case basis. Is there a reason that we might not be seeing or hearing from a certain demographic?
And perhaps most common of all…
Confounding Bias
This is the bias that relates to the well-known idea “correlation ≠ causation”.
Everyone has heard the funny examples, such as “ice cream sales cause shark attacks” (in reality, both are more likely to happen in similar places and times; when many people are at the beach, for instance).
How can any research paper possibly screw this one up?
Often they don’t and it’s a case of Spin Bias (see above), but examples that are not so obviously wrong “by common sense” often fly under the radar:
“Horse-riding found to be the sport that most extends longevity”
Should we all take up horse-riding to increase our lifespans? Probably not; the reality is that people who can afford horses can probably afford better than average healthcare, and lead easier, less stressful lives overall. The fact that people with horses typically have wealthier lifestyles than those without, is the confounding variable here.
See This And Many More Educational Cartoons on XKCD.com!
In short, when you look at the scientific research papers cited in the articles you read (you do look at the studies, yes?), watch out for these biases that found their way into the research, and you’ll be able to draw your own conclusions, with well-informed confidence, about what the study actually tells us.
Science shouldn’t be gatekept, and definitely shouldn’t be abused, so the more people who know about these things, the better!
So…would one of your friends benefit from this knowledge? Forward it to them!
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When BMI Doesn’t Measure Up
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When BMI Doesn’t Quite Measure Up
Last month, we did a “Friday Mythbusters” edition of 10almonds, tackling many of the misconceptions surrounding obesity. Amongst them, we took a brief look at the usefulness (or lack thereof) of the Body Mass Index (BMI) scale of weight-related health for individuals. By popular subscriber request, we’re now going to dive a little deeper into that today!
The wrong tool for the job
BMI was developed as a tool to look at large-scale demographic trends, stemming from a population study of white European men, who were for the purpose of the study (the widescale health of the working class in that geographic area in that era), considered a reasonable default demographic.
In other words: as a system, it’s now being used in a way it was never made for, and the results of that misappropriation of an epidemiological tool for individual health are predictably unhelpful.
If you want to know yours…
Here’s the magic formula for calculating your BMI:
- Metric: divide your weight in kilograms by your height in square meters
- Imperial: divide your weight in pounds by your height in square inches and then multiply by 703
“What if my height doesn’t come in square meters or square inches, because it’s a height, not an area?”
We know. Take your height and square it anyway. If this seems convoluted and arbitrary, yes, it is.
But!
While on the one hand it’s convoluted and arbitrary… On the other hand, it’s also a gross oversimplification. So, yay for the worst of both worlds?
If you don’t want to grab a calculator, here’s a quick online tool to calculate it for you.
So, how did you score?
According to the CDC, a BMI score…
- Under 18.5 is underweight
- 18.5 to 24.9 is normal
- 25 to 29.9 is overweight
- 30 and over is obese
And, if we’re looking at a representative sample of the population, where the representation is average white European men of working age, that’s not a bad general rule of thumb.
For the rest of us, not so representative
BMI is a great and accurate tool as a rule of thumb, except for…
Women
An easily forgotten demographic, due to being a mere 51% of the world’s population, women generally have a higher percentage of body fat than men, and this throws out BMI’s usefulness.
If pregnant or nursing
A much higher body weight and body fat percentage—note that these are two things, not one. Some of the extra weight will be fat to nourish the baby; some will be water weight, and if pregnant, some will be the baby (or babies!). BMI neither knows nor cares about any of these things. And, this is a big deal, because BMI gets used by healthcare providers to judge health risks and guide medical advice.
People under the age of 16 or over the age of 65
Not only do people below and above those ages (respectively) tend to be shorter—which throws out the calculations and mean health risks may increase before the BMI qualifies as overweight—but also:
- BMI under 23 in people over the age of 65 is associated with a higher health risk
- A meta-analysis showed that a BMI of 27 was the best in terms of decreased mortality risk for the over-65 age group
This obviously flies in the face of conventional standards regards BMI—as you’ll recall from the BMI brackets we listed above.
Read the science: BMI and all-cause mortality in older adults: a meta-analysis
Athletic people
A demographic often described in scientific literature as “athletes”, but that can be misleading. When we say “athletes”, what comes to mind? Probably Olympians, or other professional sportspeople.
But also athletic, when it comes to body composition, are such people as fitness enthusiasts and manual laborers. Which makes for a lot more people affected by this!
Athletic people tend to have more lean muscle mass (muscle weighs more than fat), and heavier bones (can’t build strong muscles on weak bones, so the bones get stronger too, which means denser)… But that lean muscle mass can actually increase metabolism and help ward off many of the very same things that BMI is used as a risk indicator for (e.g. heart disease, and diabetes). So people in this category will actually be at lower risk, while (by BMI) getting told they are at higher risk.
If not white
Physical characteristics of race can vary by more than skin color, relevant considerations in this case include, for example:
- Black people, on average, not only have more lean muscle mass and less fat than white people, but also, have completely different risk factors for diseases such as diabetes.
- Asian people, on average, are shorter than white people, and as such may see increased health risks before BMI qualifies as overweight.
- Hispanic people, on average, again have different physical characteristics that throw out the results, in a manner that would need lower cutoffs to be even as “useful” as it is for white people.
Further reading on this: BMI and the BIPOC Community
In summary:
If you’re an average white European working-age man, BMI can sometimes be a useful general guide. If however you fall into one or more of the above categories, it is likely to be inaccurate at best, if not outright telling the opposite of the truth.
What’s more useful, then?
For heart disease risk and diabetes risk both, waist circumference is a much more universally reliable indicator. And since those two things tend to affect a lot of other health risks, it becomes an excellent starting point for being aware of many aspects of health.
Pregnancy will still throw off waist circumference a little (measure below the bump, not around it!), but it will nevertheless be more helpful than BMI even then, as it becomes necessary to just increase the numbers a little, according to gestational month and any confounding factors e.g. twins, triplets, etc. Ask your obstetrician about this, as it’s beyond the scope of today’s newsletter!
As to what’s considered a risk:
- Waist circumference of more than 35 inches for women
- Waist circumference of more than 40 inches for men
These numbers are considered applicable across demographics of age, sex, ethnicity, and lifestyle.
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Lies I Taught in Medical School – by Dr. Robert Lufkin
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There seems to be a pattern of doctors who practice medicine one way, get a serious disease personally, and then completely change their practice of medicine afterwards. This is one of those cases.
Dr. Lufkin here presents, on a chapter-by-chapter basis, the titularly promised “lies” or, in more legally compliant speak (as he acknowledges in his preface), flawed hypotheses that are generally taught as truths. In many cases, the “lie” is some manner of “xyz is normal and nothing to worry about”, and/or “there is nothing to be done about xyz; suck it up”.
The end result of the information is not complicated—enjoy a plants-forward whole foods low-carb diet to avoid metabolic diseases and all the other things to branch off from same (Dr. Lufkin makes a fair case for metabolic disease leading to a lot of secondary diseases that aren’t considered metabolic diseases per se). But, the journey there is actually important, as it answers a lot of questions that are much less commonly understood, and often not even especially talked-about, despite their great import and how they may affect health decisions beyond the dietary. Things like understanding the downsides of statins, or the statistical models that can be used to skew studies, per relative risk reduction and so forth.
Bottom line: this book gives the ins and outs of what can go right or wrong with metabolic health and why, and how to make sure you don’t sabotage your health through missing information.
Click here to check out Lies I Taught In Medical School, and arm yourself with knowledge!
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Can You Step Backwards Without Your Foot Or Torso Turning Out?
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Walking backwards is often overlooked, but research shows it can enhance forward walking, especially in stroke patients; it has other benefits for everyone else, too. The physiotherapists at Fitness4Life Physical Therapy explain:
…and one step back
How it works: walking backwards heightens proprioception and stimulates muscles, improving balance and posture. Additionally, our daily lives tend to involve forward-leaning postures, causing upper back bending, and walking backwards helps counterbalance this.
Extra benefits: training to walk backwards can reduce the risk of falls, as stepping back is a common movement that is often untrained.
Exercise: try doing backwards lunges, to assess your skill and balance while moving backward. If foot rotation or torso rotation occurs during the exercise, then there’s room for improvement. Correcting these movements is then simply a matter of practicing backward lunges without turning.
10almonds tip: any exercise is only as good as your will to actually do it. For this reason, dancing is a great exercise in this case, as almost all forms of dance involve stepping backwards (in order to have steps without travelling somewhere, forwards steps are usually balanced with backwards ones)
For more on all this, plus a visual demonstration of the exercise, enjoy:
Click Here If The Embedded Video Doesn’t Load Automatically!
Want to learn more?
You might also like to read:
Fall Special ← About how to avoid falling, and how to avoid (and failing that, at least minimize) injury if you do fall. If you think this only happens to other/older people, remember, there’s a first time for everything, so it is better to be prepared in advance!
Take care!
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What are heart rate zones, and how can you incorporate them into your exercise routine?
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If you spend a lot of time exploring fitness content online, you might have come across the concept of heart rate zones. Heart rate zone training has become more popular in recent years partly because of the boom in wearable technology which, among other functions, allows people to easily track their heart rates.
Heart rate zones reflect different levels of intensity during aerobic exercise. They’re most often based on a percentage of your maximum heart rate, which is the highest number of beats your heart can achieve per minute.
But what are the different heart rate zones, and how can you use these zones to optimise your workout?
The three-zone model
While there are several models used to describe heart rate zones, the most common model in the scientific literature is the three-zone model, where the zones may be categorised as follows:
- zone 1: 55%–82% of maximum heart rate
- zone 2: 82%–87% of maximum heart rate
- zone 3: 87%–97% of maximum heart rate.
If you’re not sure what your maximum heart rate is, it can be calculated using this equation: 208 – (0.7 × age in years). For example, I’m 32 years old. 208 – (0.7 x 32) = 185.6, so my predicted maximum heart rate is around 186 beats per minute.
There are also other models used to describe heart rate zones, such as the five-zone model (as its name implies, this one has five distinct zones). These models largely describe the same thing and can mostly be used interchangeably.
What do the different zones involve?
The three zones are based around a person’s lactate threshold, which describes the point at which exercise intensity moves from being predominantly aerobic, to predominantly anaerobic.
Aerobic exercise uses oxygen to help our muscles keep going, ensuring we can continue for a long time without fatiguing. Anaerobic exercise, however, uses stored energy to fuel exercise. Anaerobic exercise also accrues metabolic byproducts (such as lactate) that increase fatigue, meaning we can only produce energy anaerobically for a short time.
On average your lactate threshold tends to sit around 85% of your maximum heart rate, although this varies from person to person, and can be higher in athletes.
In the three-zone model, each zone loosely describes one of three types of training.
Zone 1 represents high-volume, low-intensity exercise, usually performed for long periods and at an easy pace, well below lactate threshold. Examples include jogging or cycling at a gentle pace.
Zone 2 is threshold training, also known as tempo training, a moderate intensity training method performed for moderate durations, at (or around) lactate threshold. This could be running, rowing or cycling at a speed where it’s difficult to speak full sentences.
Zone 3 mostly describes methods of high-intensity interval training, which are performed for shorter durations and at intensities above lactate threshold. For example, any circuit style workout that has you exercising hard for 30 seconds then resting for 30 seconds would be zone 3.
Striking a balance
To maximise endurance performance, you need to strike a balance between doing enough training to elicit positive changes, while avoiding over-training, injury and burnout.
While zone 3 is thought to produce the largest improvements in maximal oxygen uptake – one of the best predictors of endurance performance and overall health – it’s also the most tiring. This means you can only perform so much of it before it becomes too much.
Training in different heart rate zones improves slightly different physiological qualities, and so by spending time in each zone, you ensure a variety of benefits for performance and health.
So how much time should you spend in each zone?
Most elite endurance athletes, including runners, rowers, and even cross-country skiers, tend to spend most of their training (around 80%) in zone 1, with the rest split between zones 2 and 3.
Because elite endurance athletes train a lot, most of it needs to be in zone 1, otherwise they risk injury and burnout. For example, some runners accumulate more than 250 kilometres per week, which would be impossible to recover from if it was all performed in zone 2 or 3.
Of course, most people are not professional athletes. The World Health Organization recommends adults aim for 150–300 minutes of moderate intensity exercise per week, or 75–150 minutes of vigorous exercise per week.
If you look at this in the context of heart rate zones, you could consider zone 1 training as moderate intensity, and zones 2 and 3 as vigorous. Then, you can use heart rate zones to make sure you’re exercising to meet these guidelines.
What if I don’t have a heart rate monitor?
If you don’t have access to a heart rate tracker, that doesn’t mean you can’t use heart rate zones to guide your training.
The three heart rate zones discussed in this article can also be prescribed based on feel using a simple 10-point scale, where 0 indicates no effort, and 10 indicates the maximum amount of effort you can produce.
With this system, zone 1 aligns with a 4 or less out of 10, zone 2 with 4.5 to 6.5 out of 10, and zone 3 as a 7 or higher out of 10.
Heart rate zones are not a perfect measure of exercise intensity, but can be a useful tool. And if you don’t want to worry about heart rate zones at all, that’s also fine. The most important thing is to simply get moving.
Hunter Bennett, Lecturer in Exercise Science, University of South Australia
This article is republished from The Conversation under a Creative Commons license. Read the original article.
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Cancer is increasingly survivable – but it shouldn’t depend on your ability to ‘wrangle’ the health system
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One in three of us will develop cancer at some point in our lives. But survival rates have improved to the point that two-thirds of those diagnosed live more than five years.
This extraordinary shift over the past few decades introduces new challenges. A large and growing proportion of people diagnosed with cancer are living with it, rather than dying of it.
In our recently published research we examined the cancer experiences of 81 New Zealanders (23 Māori and 58 non-Māori).
We found survivorship not only entailed managing the disease, but also “wrangling” a complex health system.
Surviving disease or surviving the system
Our research focused on those who had lived longer than expected (four to 32 years since first diagnosis) with a life-limiting or terminal diagnosis of cancer.
Common to many survivors’ stories was the effort it took to wrangle the system or find others to advocate on their behalf, even to get a formal diagnosis and treatment.
By wrangling we refer to the practices required to traverse complex and sometimes unwelcoming systems. This is an often unnoticed but very real struggle that comes on top of managing the disease itself.
The common focus of the healthcare system is on symptoms, side effects of treatment and other biological aspects of cancer. But formal and informal care often falls by the wayside, despite being key to people’s everyday experiences.
The inequities of cancer survivorship are well known. Analyses show postcodes and socioeconomic status play a strong role in the prevalence of cancer and survival.
Less well known, but illustrated in our research, is that survival is also linked to people’s capacity to manage the entire healthcare system. That includes accessing a diagnosis or treatment, or identifying and accessing alternative treatments.
Survivorship is strongly related to material resources, social connections, and understandings of how the health system works and what is available. For instance, one participant who was contemplating travelling overseas to get surgery not available in New Zealand said:
We don’t trust the public system. So thankfully we had private health insurance […] But if we went overseas, health insurance only paid out to $30,000 and I think the surgery was going to be a couple of hundred thousand. I remember Dad saying and crying and just being like, I’ll sell my business […] we’ll all put in money. It was really amazing.
Assets of survivorship
In New Zealand, the government agency Pharmac determines which medications are subsidised. Yet many participants were advised by oncologists or others to “find ways” of taking costly, unsubsidised medicines.
This often meant finding tens of thousands of dollars with no guarantees. Some had the means, but for others it meant drawing on family savings, retirement funds or extending mortgages. This disproportionately favours those with access to assets and influences who survives.
But access to economic capital is only one advantage. People also have cultural resources – often described as cultural capital.
In one case, a participant realised a drug company was likely to apply to have a medicine approved. They asked their private oncologist to lobby on their behalf to obtain the drug through a compassionate access scheme, without having to pay for it.
Others gained community support through fundraising from clubs they belonged to. But some worried about where they would find the money, or did not want to burden their community.
I had my doctor friend and some others that wanted to do some public fundraising. But at the time I said, “Look, most of the people that will be contributing are people from my community who are poor already, so I’m not going to do that option”.
Accessing alternative therapies, almost exclusively self-funded, was another layer of inequity. Some felt forced to negotiate the black market to access substances such as marijuana to treat their cancer or alleviate the side effects of orthodox cancer treatment.
Cultural capital is not a replacement for access to assets, however. Māori survivorship was greatly assisted by accessing cultural resources, but often limited by lack of material assets.
Persistence pays
The last thing we need when faced with the possibility of cancer is to have to push for formal diagnosis and care. Yet this was a common experience.
One participant was told nothing could be found to explain their abdominal pain – only to find later they had pancreatic cancer. Another was told their concerns about breathing problems were a result of anxiety related to a prior mental health history, only to learn later their earlier breast cancer had spread to their lungs.
Persistence is another layer of wrangling and it often causes distress.
Once a diagnosis was given, for many people the public health system kicked in and delivered appropriate treatment. However, experiences were patchy and variable across New Zealand.
Issues included proximity to hospitals, varying degrees of specialisation available, and the requirement of extensive periods away from home and whānau. This reflects an ongoing unevenness and lack of fairness in the current system.
When facing a terminal or life-limiting diagnosis, the capacity to wrangle the system makes a difference. We shouldn’t have to wrangle, but facing this reality is an important first step.
We must ensure it doesn’t become a continuing form of inequity, whereby people with access to material resources and social and cultural connections can survive longer.
Kevin Dew, Professor of Sociology, Te Herenga Waka — Victoria University of Wellington; Alex Broom, Professor of Sociology & Director, Sydney Centre for Healthy Societies, University of Sydney; Chris Cunningham, Professor of Maori & Public Health, Massey University; Elizabeth Dennett, Associate Professor in Surgery, University of Otago; Kerry Chamberlain, Professor of Social and Health Psychology, Massey University, and Richard Egan, Associate Professor in Health Promotion, University of Otago
This article is republished from The Conversation under a Creative Commons license. Read the original article.
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