Hypothesis: hormone-mimicking plastics in the human body are causing endocrine disruption and are part of the cause of obesity epidemic.
The rise of obesity itself has many obvious causes. Sedentary work, high calorie, high sugar/sweetener diets. If it were microplastics you would expect to see this as a universal effect, but it's really not. While obesity is rising on average, it's highly concentrated. Many communities, especially affluent ones, have very low obesity rates still. Very few people in my social / work circle are obese. And like, although I've cut out soda and most of the obvious bad things, its still apparent to me that my diet is likely overloaded with sugar and sweeteners much more than past generations. Poor people have high stress, insufficient money to buy quality food, and insufficient time / hardware to invest in food preparations on a regular basis.
And we have case examples too. Remote Amazonian (brazil) populations get introduced to nestle food? Wait several years and bam, fat.
Why are pets getting fatter? Because they're eating garbage too. Why are wild animals getting fatter? Because they're eating garbage too. You then see follow up questions like "Why are sperm quality readings dropping in dogs?" It's because they're fucking fatter. "Why are sperm quality readings dropping in people that aren't obese?" Because the whole population is shifting right and is fatter within their BMI bin.
Antibiotics are a real studied cause as well of causing fattening.
Frankly it would be extremely surprising to me if we didn't see the outcomes in obesity that we are seeing given the dietary crises the world is facing. Microplastics need not appear in this picture.
I can't make sense of this statistically. Bins are just arbitrary cutoffs on a distribution. It's not like people know where the lines of bins are and crowd up against the edge, throwing off the median inside. People shifting "within" a "bin" doesn't change much. Instead, people shift bins. Some bins have more people, some bins have fewer people.
I think obesity is a huge factor, maybe 80%. But I don't know why you feel so strongly that every other explanation is completely false.
The bin argument is basically saying that if the entire population gets fatter, you would expect the average weight within a bin to go up, even if some people move into the next. This depends somewhat on the shape of the curve, and the bins. But on a whole it's simply saying that the average weight of people between X lbs and Y lbs is higher than it was before.
Really what it's saying is that the bins obfuscate what could be better analyzed as a continuous variable effect. The bins are arbitrary and misleading. People can fall within the same bin at t1 and t2 but be fatter at t2.
> I think obesity is a huge factor, maybe 80%. But I don't know why you feel so strongly that every other explanation is completely false.
The evidence and effect size is simply extremely strong, and the prevalence of obesity is very high. I estimate obesity to account for more than 90% of the sperm effect and diet to account for more than 90% of the obesity effect.
I'm not opposed to the idea that plastics might have some small single digit effect size. Nor am I opposed to the idea that we might see an inflection point where more plastics start being significantly worse. But for now, it seems to be a tiny, unimportant part of the story.
It does depend on shape of the distribution, but it is generally not the case that the average within a bin will go up. It is certainly not true for a bell curve, where if you push the curve out to the right (and flatten it), some bins will have higher averages (because they are weighted more to the right than before), but some bins will have lower averages (because they are weighted more to the left than before). If we wanted to go way deep on this, it really depends on the second derivative of the curve within a bin, not even the first derivative (a flat or even straight line through the bin will always give an average right in the middle).
Though I would assert that my premise for this particular distribution held true and that binned analyses were misleading. I tried to find the article. I could not.
This particular example was had no lower bound on the left below overweight, and was skew right with the peak of the curve in this lowest category if memory serves. I remember thinking it was visually obvious that the bin would get on average fatter but I suppose it does not generalize.
https://www.health.harvard.edu/mens-health/obesity-unhealthy...
> Obesity lowers testosterone levels. For example, a 2007 study of 1,667 men ages 40 and above found that each one-point increase in BMI was associated with a 2% decrease in testosterone. In addition, a 2008 study of 1,862 men ages 30 and above found that waist circumference was an even stronger predictor of low testosterone levels than BMI. A four-inch increase in waist size increased a man's odds of having a low testosterone level by 75%; for comparison, 10 years of aging increased the odds by only 36%. All in all, waist circumference was the strongest single predictor of developing symptoms of testosterone deficiency.
[0] https://www.forbes.com/sites/neilhowe/2017/10/02/youre-not-t...
[1] https://www.reuters.com/article/health-testosterone-levels-d...
Here's a paper by the same author: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2579652/
Table 4 has the highlights. An extra 10 years of age has an odds ratio of 1.4 and a p value of 0.02. A 10 cm increase in waist size has an odds ratio of 1.9 and a p value less than 0.001. That is to say, this same author found waist size was a stronger predictor of testosterone than age. This study occurs a few years after the one referenced in the article.
Here's the actual study which does make the claim that these factors are insufficient on their own to explain age-normalized t levels. Personally I'm not totally convinced by their methods to control here. It's surprising to me that the later cohorts studied were seemingly the same weight but had poorer health metrics for one. The initial cohort also had an age range of 47-71. The later cohort had an age range of 57-80. The average age being 10 years older. I'm not convinced their mixed effect linear model is going to get a good comparison between these too.
https://academic.oup.com/jcem/article/92/1/196/2598434?login...
When talking statistical trends, keep in mind that even animals in tightly-controlled settings are getting obese in aggregate [1]. This is scientifically curious.
[1] https://www.theatlantic.com/national/archive/2013/10/its-not...
I would speculate the issue has just been slowly progressing for the past couple decades. The same amount of negative social pressure from being 15 lbs overweight in the 90s may be closer what somebody receives at 50 lbs now.
And all the snacks we have now, existed then...
Even by Scottish standards that seemed a bit much!
Can you increase your caloric intake by 24% without putting on weight?
edit: src https://www.businessinsider.com/daily-calories-americans-eat...
Whereas plastics -- When you look at the staggering amount of plastics pollution coming out of rivers in East and South East Asian and the subcontinent, it correlates pretty well with some of the lowest obesity rates in the world.
I think the effects of the unlimited-refills thing, and (relatedly) of to-go soda cup sizes becoming insanely large, doesn't explain the whole thing but probably is a big enough factor to be worth looking at.
HFCS increases obesity. But you have increasing obesity in regions without it, and have people who eat it who aren’t obese. It’s neither necessary nor sufficient and your comment contributes nothing to evaluating the role of microplastics.
So we absolutely have the root cause, but not perhaps the only one.
Obesity is not caused by a vast availability of calories. It is caused by a breakdown in the bodies ability to match caloric input with output.
To be clear, vast amounts of added sugar seem to cause this system to breakdown, but the mechanism is more complicated than simple calories available in the environment.
Not a breakdown. The human body is just way too efficient. Absurdly so. Humans can exercise for hours and not burn 1000 kcal but it takes mere minutes to ingest that many calories.
That’s how you end up with serious athletes on 8-10,000 calorie diets.
For a 25 year old 5’10” male living a sedentary lifestyle the difference between 160lb and 200lb is ~2,060 vs 2,278 calories or about a 10% surplus. A more active lifestyle increase that difference ~3,262 vs 3,607 is about 380 calories per day or a 12% surplus.
Though I suspect the average obese person is significantly more than 40lb overweight. At 300lb he needs ~2,822 or roughly a 40% surplus while sedentary.
What else has changed in human behaviour since, say 1900?
Cars? Americans drive everywhere. Europeans, not so much.
The rise of offices and people working less laborious jobs?
It's both sides, energy in (more sugar than in 1900 by a massive margin), and energy out (a more sedentary life style).
And here we are in 2022.
Sugar is easily stored by the body as fat, so when in > out, it's fat++
Sounds like a good argument for climate sceptics.
There's plenty of evidence about harms of sugar: https://www.hsph.harvard.edu/nutritionsource/healthy-drinks/....
Leave fossil fuels in the ground. That's it. The end.
(Sorry maybe you can't have your SUV)
Processed or sugar laden foods may be the culprit but the science isn't at all settled.
Maybe in the past, but these days when I do grocery shopping in Poland, most products have it
At least in the UK, we consume very little HFCS, but we are one of the European nations closest behind the US on the obesity scale.
No idea how much HFCS you have in Poland, but you're relatively thin compared to us, so if you have more HFCS.. possibly points the finger at something other than HFCS content.
Also it's interesting that pets, lab animals and city wildlife are getting fat globally too on a similar curve to humans.
Another hypothesis: Endocrine disruptors in pregnancy lead to damages in the endocrine system and development of children, and contribute to some of the issues many people are nowadays facing.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7967748/
>> In a further study, following 28 days exposure by oral gavage (100 μL PS-MPs (10 mg/mL)) PS-MPs (0.5, 4, 10 μm) bioaccumulate in mice testis altering spermatogenesis progression, SPZ morphology, testosterone biosynthesis and body weights and inducing inflammatory response [73]; interestingly, in vitro MPs enter into germ cells, Sertoli and Leydig cells [73].
There are sibling comments elsewhere in this thread that go into much greater detail than I can about how the link between plastic and fertility is tenuous at best. But the most significant piece of evidence against it IMO is that plastics are more or less evenly distributed. You don't have a lot more exposure at various socio-economic levels. But higher socio-economic class has a distinct negative correlation with obesity.
The (US) obesity epidemic comes from a food landscape obsessed with sugar. Most things you will find in supermarkets and restaurants are just significantly more calorically dense than it needs to be. That's your cause. The epidemic comes from eating too much.
Pointing fingers at other things might be useful, after the biggest issue is tackled.