Bad Math Strikes Again- Part 2- Vicious Vaccines

A friend of a friend who has since friended me on Facebook shared one of their friend's posts today about autism's rising rates in children in recent years. The friend of a friend of a friend (have I lost you yet?) made the bold statement that by 2022, 1 in 9 eight-year-olds will be diagnosed as autistic! This person, hereafter referred to as RD for Random Dudette, photographed and uploaded images of their math to prove this number was correct. The data they used came from the CDC website and showed the prevalence of autism in 8-year-olds for the years 2000, 2002, 2004, 2006, and 2008. Here is that data for easy reference:

In 2000- they found 6.7 out of every 1000 eight-year-olds had autism- this is about 1 in 150

In 2002- they found 6.6 out of every 1000 eight-year-olds had autism- this is about 1 in 150

In 2004- they found 8.0 out of every 1000 eight-year-olds had autism- this is about 1 in 125

In 2006- they found 9.0 out of every 1000 eight-year-olds had autism- this is about 1 in 110

In 2008- they found 11.3 out of every 1000 eight-year-olds had autism- this is about 1 in 88

Unfortunately, RD removed the post after I pointed out what the correct figure was but before I could fully document why her number was wrong, but the main issues, so that others may not make similar errors, were the following:

- She only observed 2 data points out of the 5 given. Her start point was 2002 and her end point was 2008. I never got a straight answer as to why she did not start with 2000 and use the full range of the data (I assume it was because a decrease in the autism rate between 2000 and 2002 went against the point she was trying to make)

- She extrapolated that there was a 72% increase in the autism rate between 2002 and 2008, a fact that is actually true but misleading, and used that to determine that autism rates were increasing by 13% each year. The calculated a projected 2022 rate based on a 13% yearly increase.

Here is the truth: This data says little to nothing about the future of autism rates!

The sampling is relatively small, doesn't take into account the changing definition of autism or new diagnosing techniques, and has no apparent trend. To give you a better idea, here is another way to look at the data:

2000—0.67%

2002—0.66% down .01% from 2000

2004—0.80% up .14% from 2002

2006—0.90% up .10% from 2004

2008—1.13% up .23% from 2006

This shows the percentage of eight-year-olds with diagnosed autism in each surveillance year (these numbers are each found by dividing the number of children per thousand by 1000[i.e. 6.7/1000=0.0067] and then multiplying that number by 100 to get the percent [i.e. 0.0067x100=0.67%])

We see two things from this new way of looking at things. First of all, the total percent of change from 2000 to 2008 is .46%. When divided by 8 this number becomes 0.0575% per year in increase on average. But looking at the data we see only that the rate appears to be increasing at a rate of less than .25% but more than -.01% every two years. The range appears rather large considering how small the autism rate currently is, but we would need much more data to determine if that were the case.

The problem with RD (and I will use her numbers here, not mine) is that she lays one statistic on top of another which very easily confuses people. The statistic 1.13 is, in fact, a 72% increase over .66 (1-1.13/.66) but this is a percent of change, not the actual change that occurred over the 6 years. The actual change is .47% (1.13-.66). This means the yearly average percent of change was about 12% but yearly average rate of change is just .0783% using RD's own numbers.

Now to throw out some bullshit statistics of my own. If I were to assume that the average yearly rate of change I calculated earlier (with my own numbers, not RD's) would hold true for the next 14 year, which they won't for so many reasons I won't bother mentioning, here is what 8-year-old autism rates would look like over the next 14 years:

2009—1.1875% which is 11.9 out of 1000 and equates out to 1 in 84.0336

2010—1.245% which is 12.5 out of 1000 and equates out to 1 in 80

2011—1.3025% which is 13.0 out of 1000 and equates out to 1 in 76.9231

2012—1.36% which is 13.6 out of 1000 and equates out to 1 in 73.5294

2013—1.4175% which is 14.2 out of 1000 and equates out to 1 in 70.4225

2014—1.475% which is 14.8 out of 1000 and equates out to 1 in 67.5676

2015—1.5325% which is 15.3 out of 1000 and equates out to 1 in 65.3595

2015—1.5895% which is 15.9 out of 1000 and equates out to 1 in 62.8931

2017—1.647% which is 16.5 out of 1000 and equates out to 1 in 60.6061

2018—1.7045% which is 17.0 out of 1000 and equates out to 1 in 58.8236

2019—1.762% which is 17.6 out of 1000 and equates out to 1 in 56.8182

2020—1.8195% which is 18.2 out of 1000 and equates out to 1 in 54.9451

2021—1.877% which is 18.8 out of 1000 and equates out to 1 in 53.1915

2022—1.9345% which is 19.3 out of 1000 and equates out to 1 in 51.6929

This means, to contrast RD's 1 in 9 figure, that my doomsday prediction is that in 2022 one out of every fifty-two 8-year-olds will be diagnosed as autistic. That is still less than 2% of the 8-year-old population, but it is not a number that I would ever want to see a reality. When I gave RD my figures earlier today she said "What does it matter if the number is 1 in 9 or 1 in 51?" 

The truth is that there is a huge difference between a 10% chance and 2% chance, even in a mock situation 10 years in the future. RD's outrageous numbers do nothing more than stir up panic and anger in a crowd that is already on edge from dealing with a child with autism. If my numbers are bullshit then her numbers are elephant shit and, when dealing with a lazy and/or uneducated audience, these numbers are nothing but inflammatory propaganda to support the cause against vaccines.

The cool reality, in my eyes, is that autism is on the rise. Better reporting/diagnosis and the expansion of the definition of Autism (creation of the term ASD- Autism Spectrum Disorder) can account for a large amount of the increase from the first reporting date in 1980 where it was said 1 in 10,000 people were autistic. But now, with these conditions in place for over a decade, we should be seeing a leveling out of the number of cases. Instead the numbers appear to be continuing to rise and this suggests that there is something else causing it. 

The reason why is still unknown. It could be environmental, dietary, evolutionary, or there is a chance it could be related to a vaccine as many people think. The truth is we don't know, but when it comes to vaccines we must weigh our odds and determine the best choice for ourselves and our children. The reality is this, before the MMR vaccine 2.6 million people died each year as a result of measles, in 2008 only 164,000 people died and most of those were children in developing countries where the vaccine is not yet available or widespread. Mumps can cause deafness or meningitis (a swelling/infection of the brain or spinal column) but is not typically fatal, nor is the rubella virus unless it is contracted congenitally while in utero in which case the prognosis is bad. Rubella used to have wide spread outbreaks on a regular basis until the vaccine was introduced and now cases are nearly non-existent in developed countries where the vaccine is wide spread. Compare all those odds to the less than 1% chance, if that since no link has ever been proven, of your child getting autism. Also, consider small pox, which now exists only in a frozen lab somewhere because of widespread vaccination, and the millions of people who are alive because of it.

I would not wish autism on any parent, but it is irresponsible to not vaccinate your child for fear of one disease when the disease you leave your child exposed to could be so much worse, especially when your fear is not grounded on any solid facts. Anyone who believed, or still believes, RD's inflated numbers gets a whopping 8 on the FT scale in my book. Anti-vaccine nut jobs in general get a 6 because anyone who will criticize the medical community's use of vaccines without obtaining any solid evidence, and no your gut feeling doesn't count as evidence, to contradict them needs to pull their head out of their ass and stop blaming everyone else for their problems.

Bad Math Strikes Again- Part 1- Fat, Lazy Americans

Today has been wrought with bad math in important subjects where people should not be misled so I'm going to do another double down day and post on both, starting with the one that's made me less angry. This less aggravating topic comes from an article on msn.com found here.

The article is discussing the obesity problem in America and breaks down what are considered the 10 most obese cities/metro areas in the nation. Their goal is apparently to create a hall-of-shame for these struggling metro areas. It also flaunts the government's lofty goal, set in 2010, to reduce the national obesity rate from 1/3 of all Americans down to just 15%. How does the government plan to accomplish this goal? The only effort listed in the article is a list of 70 ways to prevent and control childhood obesity published in 2010. More importantly, since when is it the government's job to control the weight of its citizens? And by extension what we eat, how much, and when we eat it?

Here are some numbers for you to chew on:

City	Obesity rate	Health care costs	Resident population	Diabetes rate	Poverty rate
Reading, PA	32.7%	$190.2	88,000	10%	35%
Kennewick-Pasco-Richland, WA	33.2%	$116.5	No data	No data	No data
Topeka, KS	33.3%	$109.8	127,473	No data	No data
Lakeland-Winter Haven, Florida	33.5%	$279.3	No data	No data	No data
Charleston, West Virginia	33.8%	$146.9	51,000	17%	No data
Beaumont-Port Arthur, Texas	33.8%	$182.8	No data	No data	No data
Rockford, Illinois	35.5%	$179.4	152,000	10%	23%
Huntington-Ashland, West Virginia-Kentucky-Ohio	36%	$146.9	No data	20%	No data
Binghamton, New York	37.6%	$131.5	45,000	No data	27.8%
McAllen-Edinburg-Mission, Texas	38.8%	$410.9	No data	No data	No data
National Rates (gathered independently from the article)	35.7%	?	311 million	8.5%	15.1%

Health care costs are all represented in millions of dollars. This data, except the final row, comes directly from the article.

There are a few important things to note in this table:
1) all but three of the obesity rates are actually under the national figure (which I obtained from the CDC website)
2) all of the cities with data on the resident population are relatively small populations which makes this number more easily skewed in one direction or the other
3) only Lakeland-Winter Haven and McAllen-Eidenburg-Mission have health care costs above $200 million and, in the case of Lakeland-Winter Haven, this may be attributed to other circumstances such as a much larger elderly population. McAllen-Edinburg-Mission's health care costs are so much higher than any of the other cities with similar obesity rates that it is likely that this city also has some other condition that is effecting the health of its people.
4) the metro area with the second highest obesity rate has the third lowest of the 10 areas as far as health care costs, probably due to the extremely small population

Other than the numbers being rather inconclusive, I have several other issues with this article, and the panic over the "epidemic" of obesity in general.

My first issue is the most generalized and concerns how we judge one person to be obese and another person not. I'm talking about the BMI scale. Now, there are actually many different BMI graphs and calculators circulating out there but the concept is that you calculate between your weight, height, and in some cases gender and age, and are given a label such as under-weight, normal, over-weight, and obese. The scale does not take into account any other important factors that can affect weight such as ethnicity, and muscle tone/mass, it just assigns you a label and you become another statistic.

It would be one thing if the BMI labels were fairly liberal to account for the inaccuracy of the scale. The problem with the BMI is that, looking at the various graphs, there seem to be some rather radical determinations. In one graph I found, if you are 6' tall and weigh 135 lbs you are considered normal but if you are 5' tall and 130 lbs you are considered over-weight. In another graph, if you're 6'3" and 200 lbs you're bordering on obese and if you're 4'11" and over 120lbs you are over-weight. It's bad enough that the media idolizes women who look as if, and sometimes do, starve themselves in the name of beauty. Now the medical professions is labeling people as "over-weight" when they are otherwise healthy, active individuals.

The next issue I have with the article regards the health care costs, specifically the estimated savings for each metro area if they drop down to just a 15% obesity rate. Notes 3 and 4 on my table begin to touch on this but I would like to expound on it further by saying that there is no way to accurately predict the amount of health care costs that go specifically to treating complications from obesity. Doctor's don't bill an illness as "obesity" (except maybe in the case of stomach staples). The human body is a complex organism and a myriad of factors contribute to health conditions including genetics, environment, age, gender, ethnicity, and yes, weight. But the article's continued use of diabetes as a "chronic disease associated with obesity" obscures the fact that there are two different types of diabetes and they can affect thin and average people as well. The same goes for heart disease and high cholesterol. True, these illness are seen in greater prevalence among those who are on the heavier side, but they are not exclusive to those who are over-weight and their health care costs should not be treated as such. Would reducing the obesity rate result in a decrease of health care expenses? Highly likely. But the numbers are way too far into conjecture to be reported in a news article with any accuracy.

Finally, as you will note, there are many fields in the table with missing data. I understand that news writers have a limited amount of column space, but the gaps leave many questions unanswered. Were the facts left out to obscure data that contradicts with the overall trend or was it just left out to preserve space? The concluding paragraph of the article makes me concerned:

The Gallup-Healthways Well-Being Index results are based on telephone interviews throughout 2011, with a random sampling of 353,492 adults living in the U.S. Health-care costs were based on the National Institute of Health’s estimate of $1,429 per person, per year, in additional health-care costs for people considered obese, compared to those of non-obese individuals.

The sample size is very telling to me. It is 0.1% of the national population that they are drawing on to make the determination that these ten metro areas are the most obese out of the entire nation. When divided around the country, the number of people polled for these particular locations must have been very small (probably less than 100 in many cases). They list no margin of error in the article or how many people were polled in each metro area so I'm going to have to call bull-shit.

Overall, this article gets a 3 on my FT Scale for both people who read it and take it at face value and the people who conducted the survey if they think there is a strong statistical significance in their data.

My Vote Doesn't Count

In most cases I would say that no matter what, every vote counts, but in the case of US presidential candidate nominations this is not the case. It is barely March, barely a fifth of the states have weighed in and already it is being presumed that Mitt Romney will be the Republican candidate this fall. Super Tuesday is just 5 days away which should more of less decide who the candidate will be but less than half of the states will have cast their votes. This is decidedly unfair to states like Utah, New Mexico, and Oregon who do not have their primaries until late May and the beginning of June.

I understand the theoretical reason why primaries and caucuses are spread out over six months. It gives candidates the chance to focus their funds and attention on individual regions to gain a greater rapport with the local population. This is a great idea, but the implementation is all wrong.

If it was so important to spread things out then why do 33 states hold these nominations between January and March but only 21 from April through June? Granted that 33 includes places like Puerto Rico, American Samoa, and the Virgin Islands that are not included in the November election, but the weighting is still disproportional. To break it up even further, there are 4 in January, 7 in February, 22 in March, 8 in April, 7 in May, and 6 in June. There is no logic to the proportions.

I can suggest 3 better plans:

1) Hold all primaries/caucuses on the same day (like every other election). This should take place approximately 1 month before the general nominating convention and candidates should use the proceeding months to campaign and strengthen their following:
     Pros: Residents of one state will not be influenced by the results of a previous outcome and the race won't be effectively over before all states have had their say.
     Cons: Candidates will not have the chance to focus on smaller chunks of the nation to gain local support. It will also increase marketing costs for candidates as they will have to release more national rather than regional ads.

2) Space state primaries evenly over the course of 6 months. This would mean approximately 26 weeks with 2-3 elections each week or doing monthly votes with 9 states voting on the same day at the end of each month. What state has which slot would be a random draw that could be done the year before so that no state winds up with a historically bad spot at the end of the line like we have now:
     Pros: States will not be stuck with their primary not being effective year after year and candidates can still focus their attention on one segment of the country at a time.
     Cons: Logistical coordination becomes very difficult, especially in states where the primary is tied to other local elections.

3) Determine primary position based on the number of delegates up for grabs moving from least to greatest number. This means the smallest states would go first and be able to set a trend but the larger states that follow would still have enough weight to make a difference in the overall outcome:
     Pros: Determines the delegates in a manner so that smaller states will not be completely overridden by their larger counterparts and delegates can still given attention to local votes.
     Cons: Does not completely remove the possibility of a race being determined before all states can have their say.

Of the three options the third is my personal favorite, followed by number one. Unfortunately I do not have the means or the power to put forth or implement any of these plans so I suppose we will have to live with the FT level 6 system we currently have in place.

The Conclusion of Moral Conundrum

My boss fired my coworker yesterday.

He pulled me aside in the morning and said he had thought about it over the weekend and decided he had to follow his instincts and was letting the person go. No room for discussion this time, and if there had been I probably would have wound up shouting at him.

I emailed my former coworker's home email from my private email and told them I was sorry to see them go and offer myself as a reference for them only to learn that my boss had more or less forbade them from even saying goodbye to me. I'm not sure if this is from fear of what I would say about our conversation last week or if he thought my former coworker would bad mouth him to me but it became fruitless in any case.

I would have posted about this yesterday but I now find myself doing my job, my coworker's, training 2 new people who started this week, coordinating an office move/rearrangement, along with dealing with my boss' usual bullshit. I will also be adding to that list job hunting in my off hours because, while it is his right to employ who he chooses, it is my right to not have to stay there and put up with his ethically questionable behavior and bad business sense.

All in all I rank his actions around an 8 on the FT scale because he not only let go a highly qualified employee for no reason but will now lose another valued member of his team because of it.

It's not Just Me, it's the Insurance Too!

So the continuing saga of my insurance battle unfolds.

Today I received a statement of charges from my doctor's office (which I called in and left 2 voicemails before reaching a person on my third call but that's another story). The doctors office says that my remaining portion, after insurance, is $500 and change. This, to remind anyone who actually read my previous post, is for a total of 6 visits, one of which was for labs only. I am doing my due diligence and go over this bill with a fine toothed comb and determine that my insurance is, in fact, screwing me over.

Of the $500 it says I owe, I believe my actual balance due is somewhere closer to $100 for various labs and missed copays. How can this be? Well the statement I received shows what insurance codes each charge was billed under. One particular code, we will call it code X, appears under three different visits as the primary charge of "office/outpatient". Under the first visit billed under this code my insurance paid $0. The 2nd visit under code X my insurance paid the balance in full. Then, under the third code X, my insurance once again decided to pay $0.

Anyone else see the problem here? My insurance is really not going to like it when I call them on it tomorrow but that's what they get for rocketing themselves up to a solid level 6 on my FT Scale, and they're damn lucky that I'm feeling generous today.

The FT Scale

I've decided that the only way to truly show my outrage at humans/entities for their stupidity, illogic, etc. is to rank them. Hence, I am introducing the Fucktard scale (FT scale for short). This is a very simple rating system from 1 to 10 with one being lowest. Points are increased based on how stupid or illogical the thing/person is both in general and during a particular event (Congress increased their FT points by even considering SOPA and PIPA). Of course, the power they hold will be considered as a multiplier when they abuse it.

The way I see it, men like Rick Santorum and Newt Gingrich rate about a 9 on the scale. The idiot electric car driver I encountered this afternoon is only about a 1 since his actions in that particular case only really effected me and the semi-truck I nearly hit. That leaves men like President Obama sitting somewhere around a 4 (which is pretty good for a politician).