Lead poisoning from eating game shot with lead core bullets?

A great many years ago, there was a game warden in El Centro, Cal that wrote about lead poisoning. He fed wounded or hurt hawks and eagles from birds he shot with a shotgun. None die, they all recovered from there wounds. The point he was making that it's a bunch of bull on lead poisoning from lead shot and bullets. California (California) has gone off there rocker on lead bullets, and shots. Their hunting licenses sale are falling so bad in the last few years, they are having a hard time making it on the funds they are getting. I quite hunting there several years ago. Haven't purchase ammo or reloading supplies there either for 10 years.

This is exactly what the liberals want in california - an end to hunting. It's all apart of the big plan, which is to get rid of guns. They like to think that coyotes and cougars can manage the deer herd, and hunting is unnecessary. If/when all the hunters just start hunting in other states, they will have what they want - right up until the time they get killed & eaten by a big cat ……..
 
Actually an honest scientific study starts off with the null hypothesis, which states that the variable introduced makes no difference one way or another. That's why studies are double blinded. At least that's how drug studies work. Those are the only ones I have supervised professionally. Shooting animals I do as a sideline ;)
The readers also have a pre-conceived belief of what the result should be instead of the intent of the research study. There are 3 research methods, quantitative (defines the variables and relationship of the variables), qualitative (defines the nature of the phenomenon to be explored), and mixed (a combination of the two). The use of hypotheses and statistical analysis is quantitative in nature. Each research method has a corresponding research design associated depending on the nature of the research under study, i.e., quantitative (experimental, quasi-experimental, correlational, etc.) and qualitative (phenomenological, narrative inquiry, case study, grounded theory, qualitative descriptive, etc.). Yes, it gets complicated and I still struggle from it.

There is "supposed" to be a set of rules and standards (ethics, unbias, objectivity, etc.) for researchers and levels of peer-reviews, publications, etc., but adherence to it is another story.

Cheers!
Each of your opening statements speak volumes. Thanks Feenix and flyguy. My head is spinning, but it's a good thing. (I think) Lol
Good stuff, both of you. Shows just how deep the rabbit hole can get.
 
The readers also have a pre-conceived belief of what the result should be instead of the intent of the research study. There are 3 research methods, quantitative (defines the variables and relationship of the variables), qualitative (defines the nature of the phenomenon to be explored), and mixed (a combination of the two). The use of hypotheses and statistical analysis is quantitative in nature. Each research method has a corresponding research design associated depending on the nature of the research under study, i.e., quantitative (experimental, quasi-experimental, correlational, etc.) and qualitative (phenomenological, narrative inquiry, case study, grounded theory, qualitative descriptive, etc.). Yes, it gets complicated and I still struggle from it.

There is "supposed" to be a set of rules and standards (ethics, unbias, objectivity, etc.) for researchers and levels of peer-reviews, publications, etc., but adherence to it is another story.

Cheers!

Nice summary.

As a statistician (technically, a statistical geneticist), I think a lot of people do not understand what it is we do. At its heart, statistics is about making decisions and assessing the risk in making a specific decision (at least for inferential statistics, prediction is different). When you set a null hypothesis, you also set an alternative hypothesis. This alternative hypothesis is the one that is aligned with your "preconceived idea", or as we call it in research, your research hypothesis. We always have a theory of what is going on, sometimes precise and sometimes less so.

Once you have your null and alternative hypothesis set, you need to design your experiment. Ideally, you create a design that accounts for other factors that could influence your study (in public health, this could be age, weight, gender, smoking status, etc.) and balance those across all of the levels of the groups you want to test (such as new drug or standard of care in a drug study). This design leaves just the effect of interest as the thing to test with your hypothesis. The statistical analysis boils down to assessing how extreme your obtained results are out of random chance. Here's where the making decisions and assessing the risk of that decision comes in: my p-value that I calculate from my test is meant to tell me how likely am I to see a result as extreme as I saw due to random chance. if the null hypothesis is true The reason we use 0.05 as our significance level is because that relates to a 1 in 20 chance of something occurring due to random chance under the assumption of the null hypothesis being true.

So, if I perform my experiment and calculate my p-value as 0.04, I do the following since my p-value is less than 0.05. I declare that I have decided to accept the alternative hypothesis (and thus reject the null hypothesis) this is my decision. My risk is that I might observe something as extreme as what I saw 1 out of 25 times if the null hypothesis was actually true, so I feel relatively confident that what I saw is real and that the alternative hypothesis is actually true.

Sometimes, we cannot conduct a designed experiment and have to conduct what is called an observational study. This is where we have access to data that is generally already collected. We can reconstruct a design to balance factors by taking selected subsets of this data (this has some degree of bias since you are selecting data to use). Alternatively, we can use all of the data, but this also has bias because certain nuisance factors will not be balanced and have unequal influence on the outcome. Drug studies are an interesting blend of design and observational in that we have a design, but accumulate patients over time to fill in that design.

Sorry to geek out on you all, but not all of us scientists lack scruples. The vast majority of us try very hard to remain objective in our research and are constantly trying to improve upon the ways we can maintain objectivity while still making the most out of the data we have since data is expensive.
 
It is an unfortunate truth that the bulk of information being promulgated on any topic whatever is tainted by an underlying political agenda. Science is the latest go-to tool used to emphasize some point or other, and it is used most by those who have the least understanding of it. It is "junk science", meaning there is nothing scientific about it. Science is the search for truth, and every conclusion is suspect. That is why every experiment should be repeatable, and consistent in result. The experimental setup is always suspect, even for the most unbiased scientist, for being inclined to produce a preferred result. Given the dominance of left-wing bias in the universities, and the propensity to cite only those results that reinforce that bias, everything they say is suspect. There is no evidence that lead ammunition has been isolated as the sole causal agent affecting the health of people who consume game animals taken with it.

Much, if not most, of the research being done in major universities is done on government grants, and the guy who is willing to "prove' what they want to see proven is the guy who gets the grant. Typically, they make the conclusion and work backwards, cherry-picking the data that proves the conclusion and discarding everything that conflicts with it. They label conflicting data as "anomalies" or results of flawed studies, and forge ahead to present their findings and collect their trophies. They like to use the phrase "all the 'scientists' are in agreement" when half are an the other half have been discredited as dissenters. The single best way to lose one's credentials as a scientist is to disagree with something that they wanted to prove. Membership in "the club" and full compliance with the club's rules is how a scientist gets to be an expert in his specialty. anthony fauci is a case in point. Nobody questions this guy, but darn near EVERYTHING he has told us has been WRONG. What's up with that ???!!!!!
 
Each of your opening statements speak volumes. Thanks Feenix and flyguy. My head is spinning, but it's a good thing. (I think) Lol
Good stuff, both of you. Shows just how deep the rabbit hole can get.

I am a continuous learner so my head is constantly spinning (and often with migraines 😇). Thanks!

Nice summary.

As a statistician (technically, a statistical geneticist), I think a lot of people do not understand what it is we do. At its heart, statistics is about making decisions and assessing the risk in making a specific decision (at least for inferential statistics, prediction is different). When you set a null hypothesis, you also set an alternative hypothesis. This alternative hypothesis is the one that is aligned with your "preconceived idea", or as we call it in research, your research hypothesis. We always have a theory of what is going on, sometimes precise and sometimes less so.

Once you have your null and alternative hypothesis set, you need to design your experiment. Ideally, you create a design that accounts for other factors that could influence your study (in public health, this could be age, weight, gender, smoking status, etc.) and balance those across all of the levels of the groups you want to test (such as new drug or standard of care in a drug study). This design leaves just the effect of interest as the thing to test with your hypothesis. The statistical analysis boils down to assessing how extreme your obtained results are out of random chance. Here's where the making decisions and assessing the risk of that decision comes in: my p-value that I calculate from my test is meant to tell me how likely am I to see a result as extreme as I saw due to random chance. if the null hypothesis is true The reason we use 0.05 as our significance level is because that relates to a 1 in 20 chance of something occurring due to random chance under the assumption of the null hypothesis being true.

So, if I perform my experiment and calculate my p-value as 0.04, I do the following since my p-value is less than 0.05. I declare that I have decided to accept the alternative hypothesis (and thus reject the null hypothesis) this is my decision. My risk is that I might observe something as extreme as what I saw 1 out of 25 times if the null hypothesis was actually true, so I feel relatively confident that what I saw is real and that the alternative hypothesis is actually true.

Sometimes, we cannot conduct a designed experiment and have to conduct what is called an observational study. This is where we have access to data that is generally already collected. We can reconstruct a design to balance factors by taking selected subsets of this data (this has some degree of bias since you are selecting data to use). Alternatively, we can use all of the data, but this also has bias because certain nuisance factors will not be balanced and have unequal influence on the outcome. Drug studies are an interesting blend of design and observational in that we have a design, but accumulate patients over time to fill in that design.

Sorry to geek out on you all, but not all of us scientists lack scruples. The vast majority of us try very hard to remain objective in our research and are constantly trying to improve upon the ways we can maintain objectivity while still making the most out of the data we have since data is expensive.


Well said, Sir! As an analyst in the Dept of the Air Force for the last 24 years, I too use statistical analysis in our continuous process improvement program/initiatives as directed by higher headquarters.

Yes, you did geek out I love it. ;) It has been a while the last time I used it but I use SPSS to figure out pValues. Cheers!
 
Question: How many ducks fly off crippled and die Now shot with steel shot compared to lead shot Then?
Was the California Condor put on the endangered species list after the lead shot bill passed? Or was it after the lead shot ban and how much lead must it consume kill it? Studies say that the Condor populations are dwindling. What are they eating now to cause this mortality?
 
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Lead poisoning from eating game killed with lead bullets? Well for decades, I've eaten a lot of game, small and large, that has been killed with pure lead bullets, cup n core, lead shot, etc, and if anyone was going to have lead poisoning from this usage, it would be me and my family.

Over the many decades, the amount of doves, quail, ducks, geese, rabbits, squirrels, turkeys, deer, elk, etc, etc, etc have been taken with lead based ammo. I cannot begin to count how many times I have bitten into small game and spit out a piece or two of lead shot, and then the many hundreds of thousands of lead bullets I have cast. Big game kills have very small areas of potential lead when compared to small game hit with numerous lead shot, so I don't even think of those.

After many decades so far, my blood lead levels are normal, so personally, I would not worry about it. Too many other things in life
 
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Question: How many ducks fly off crippled and die Now shot with steel shot compared to lead shot Then?

Oh BOY! Don't get me started on this! When we were forced to change from lead to steel, it was MADDENING to see ducks feathered in puffs and fly hundreds of yards away. Today's heavier and costlier shot is better than the old steels, but I would still prefer lead shot.
 
Me too! And of course, ear protection. Heck, I even wear gloves, eye, and ear protection when I mow or use any power tools. To me it is all about risk management.



I have the same stance. As noted, I really do not care what an individual does with the information being presented. This learner is in no position to criticize any individual's stance on the subject matter or anybody's empirical data as I do not have any personal published peer-reviewed research paper. I have nothing but respect for those that managed to have their work published (literature/article, thesis, dissertation) because it is not an easy endeavor. I have been working on my research study since June of 2017 and currently going through multi-level Academic Quality Review processes and Independent Review Board. It has been a challenging but rewarding journey and the ultimate prize is almost within reach. 😇

After 4 hours of study time since getting off work, I think a well-deserved break is in order. Cheers to all ... be safe and God bless!

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Have a shot for me!
 
I'm not a scientist but I have experience reading technological and scientific papers. That being said;

Your first link was a valid study result but it really didn't prove that animals taken with bullets were a potential source of health threatening lead poisoning. There are several points that I think make the study questionable.

1. The study says that all weapons used to take the animals were 7mm Mag rifles using 150gr cup and core style ammunition. Toward the end of the paper they mention that some of the meat used to feed the pigs with had bird shot in it. Just how accurate was their data when they claim that only bullets were used and yet they offhandedly mention that bird shot was in the meat.

2. Their experimental method was to take game killed and field dressed by average hunters to a game processor who then processed the meat and then they fed the contaminated meat (identified by radiographic methods) to pigs. They then tested the lead levels in the pigs for 8 days after being fed the meat.

A. They didn't verify that the meat that they turned in was the same meat that they received from the processors - could that explain why they found shotgun pellets in some of the meat that was, supposedly, all taken with 7mm Mag rifles.​
B. They fed the pigs almost 3 pounds of meat in one 24 hour day. Even accounting for the weight differences between the pigs and the average person, that would mean that we would have to eat around 1 1/2 lbs of contaminated meat in one day. Who eats 1 1/2 lbs of meat in a day. And even if you do eat that much meat in a day, how much would actually be contaminated with lead from a kill, I suspect not as much as what those pigs were fed.​
C. Their final conclusion was that the pigs that ate the contaminated meat showed lead blood levels of as high as 3.8 micro-gram/dL for one pig with an average of around 2.2 micro-gram/dL . The report states that the CDC says that lead blood levels in children becomes dangerous at 10 micro-gram/dL . What's more, the pigs only showed the higher levels for the about 3 days after ingesting the meat. So, in order to reach the CDC level that is dangerous for a child, the child would have to eat an average of 5 1/2 lbs of meat in a 24 hour period every three days in order to sustain a health threatening blood lead level. For an adult we would probably have to eat much more. And we would have to ensure that all of that meat was contaminated with lead. I find that pretty hard to imagine.​

I couldn't get to your second link, I don't know if it is dead or if my security software prevented me from getting to it but I couldn't check it out.

Your third link required me to pay for the report and I'm not about to do that so I couldn't read it but the summary that was available for free states that the report concludes that


That's not really anything that seems to be news to anybody that hunts game nor does it seem to conclude that eating game could cause lead poisoning.

Your fourth link doesn't really prove anything, it's just a summary of other papers and studies, it's simply a reference resource for the The Minnesota Department of Natural Resources (MDNR). Quoting from other studies doesn't prove anything without including the process and conclusions.
I think you guys are really splitting straws, properly clean your meat,if you are worried use lead free bullets.
 
Is this a thing?? Sounds nuts to me, but a member of this forum is claiming its dangerous. I have checked with google and couldn't find anything substantive to support the claim.

How on earth has the human race survived since the creation of gunpowder. I'm thinking that for nearly 500 years game has been taken with lead projectiles from firearms. In my lifetime, the majority of shot pellets were lead. I've come to the conclusion that scientists or persons with an agenda create many nit picking issues to further their own personal goals. We seem to face a plethora of crises which threaten the extinction of the human race.

The prophets of doom, they walk among us.
 
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