Temporal epidemiology

[Conductor71]

You are saying that if Parkinsonism can be correlated to inhaled toxins, then more PD would have been more prevalent throughout history? I am not sure what you mean. I do not think this is the only path to PD but just the only one, other than viral infection, that could connect us over a big span of time , but still within the context of Rick's thoughts on fallout of the Industrial Revolution.

The toxic soup we now breath is far different in content (pre automobile) and is far more pervasive. Plus, it is grossly unregulated. I think there is a huge difference between what was inhaled by cave dwellers using fire to what is inhaled when a Teflon pan overheats. Dupont had lots of explaining to do when people started losing their pet birds. They are still allowed to sell the crap but have added a disclaimer for the family parakeet.

As for life expectancy rates comparison, yes more people were lost to unsanitary living conditions and or no antibiotics, but I don't think we can make a direct comparison. It is common knowledge that life span has increased with vaccination and use of antiobiotics, but in this regard from an evolutionary perspective we all equally benefit from those things. We negate this gain by embracing "progress". We are exposing the human body to things it is not designed to handle, and we are the sorry outcome. We have a message no one wants to hear. I could cite numerous resources linking air pollution and disease, but I cannot be more clear than this doctor with the Physicians for Socially Responsible Medicine


The systemic inflammation caused by particulate pollution also affects the brain. Air pollution components reach the brain not only through the vascular system, but translocate via the nasal mucosa, along axons of the olfactory and trigeminal nerves into the central nervous system (CNS), allowing deep penetration into the parenchyma and brain stem (35, 36). Furthermore, many of the compounds adsorbed to particulate matter, like heavy metals, are neurotoxic. Through this mechanism, particulate pollution causes CNS oxidative stress, neuroinflammation, neuronal damage, cortical stress measured by EEG, enhancement of Alzheimer type-abnormal filamentous proteins, BBB changes, and cerebrovascular damage. Many of these changes can be found in children and young adults. Greater air pollution exposure is associated with lower intelligence, poorer motor function, attention deficits and behavioral problems in children, decreased cognition in adults, higher rates of strokes, multiple sclerosis, autism, Parkinson's and other neurodegenerative diseases (37, 38, 39, 40, 41, 42, 43, 44).


I hope this addresses what you mean?

[soccertese]

your're preaching to the chorus laura, there's ample evidence that man made chemicals cause all sorts of diseases in humans and animals. kind of why we have the FDA, EPA.
almost impossible to get highly profitable chemicals banned without tremendously strong evidence. noone wants to put DOW, MONSANTO, BAYER, CHEVRON, DUPONT, etc. out of business.

my point was i didn't think the pre-industrial revolution environment was all that pristine 24hrs/day, 12months/year and pd likely existed.

[reverett123]

I agree that it existed, but think it reasonable to assume that it became markedly worse and continues to "evolve" even now. The ultra-fine particulates are obvious suspects and are a little bit frightening once one takes a close look. They are "nanoparticles" and we are just now beginning to appreciate what a threat they may pose. For one thing they are so small that traditional barriers such as the BBB and the similar one lining the gut are pretty much ineffective. These guys are so small that a neuron looks like a super highway to them and they move along in both directions. They also are able to latch onto larger molecules and transport them across those barriers as well. As an irritant alone they are a constant source of inflammation plus they go deep into our lungs. They are, indeed, produced by burning wood but the smallest come from coal and diesel smoke. And they travel far with the wind. One area is called the "Alaskan Rectangle of Death" because global wind conentrates them north of Fairbanks. And remember that if the hypothyses (sp?) that I push is correct and it is about an inflammatory response to a number of possible triggers, that they would interact with most others to multiply their effects.
Rick

Originally Posted by soccertese

your're preaching to the chorus laura, there's ample evidence that man made chemicals cause all sorts of diseases in humans and animals. kind of why we have the FDA, EPA.
almost impossible to get highly profitable chemicals banned without tremendously strong evidence. noone wants to put DOW, MONSANTO, BAYER, CHEVRON, DUPONT, etc. out of business.

my point was i didn't think the pre-industrial revolution environment was all that pristine 24hrs/day, 12months/year and pd likely existed.

[johnt]

One way to mine data is to analyse past values to see if there are trends or cycles in the data or whether there are temporal correlations with other variables. I've made a start by looking at 12 years, 1999 to 2010, of monthly US mortality data.

The data comes from the multiple causes of deaths, Wonder database at the CDC.

The graph below shows the raw PD data (blue, lefthand scale) and raw all cause data (red righthand scale). The most noticeable features are:
- the variability from month to month;
- the values go through an annual cycle: high in winter, low in summer;
- the PD and all cause numbers follow similar patterns.



In the results shown below, the following terms are used:
PD: number of deaths with Parkinson's Disease as one of the multiple causes.
ALL: number of deaths from any cause.
DELTA: PD - ALL
RAW: unprocessed data from the query shown in the Data section.

1. Basic monthly statistics.
RAW PD: mean=2822, min=2156, max=3673
RAW ALL: mean=202611, min=180153, max=247828

2. Seasonality, distribution of deaths by month.
INDEX: processed data taking into account the number of days in each month, shown as an index centred on 100. For instance, if you had just January and February data from two years, the raw data could be Jan=310, Feb=280, whereas the index for both is 100.
SEQ: 12 values, one for each month, in order from January to December.
INDEX PD: mean = SEQ(115.6, 112.9, 108.9, 99.1, 93.1, 88.6, 88.2, 88.0, 92.6, 99.0, 103.4, 111.2)
INDEX ALL: mean= SEQ(110.2, 109.3, 106.3,100.4, 96.4, 94.2, 93.2, 92.5, 93.9, 97.4, 99.9, 106.6)
INDEX DELTA: mean = SEQ(5.4, 3.6, 2.6, -1.4, -3.3, -5.6, -5.0, -4.5, -1.2, 1.6, 3.5, 4.6)
Both the all cause and the PD mortality rates are higher in the winter than in the summer. (It would be interesting to know whether this is true in the southern states.) PD shows more seasonality than the all cause data.

3. Trend.
RAW PD: trend = +0.74%/year
RAW ALL: trend = +0.12%/year
Needs analysis, but I think this is most likely due to the ageing population, linked to the increasing prevalence with age of PD.

Statistical software
The calculations were done using a programming language called r (a free version of the long standing statistical programming language s). Its advantage is that it has an enormous library of statistical functions.

Data
The data comes from the Wonder database at the CDC. The database queries are shown in the Appendix.

Wonder does not require any programming skill to use. It is an excellent system, which I recommend to anyone with an interest in epidemiology. Although on this occasion I used a different approach, you can export the results in a file which can be imported into Excel.

"Dataset: Multiple Cause of Death, 1999-2010"
"Query Parameters:"
"Title:"
"Autopsy: All"
"Gender: All"
"Hispanic Origin: All"
"MCD - ICD-10 Codes: G20 (Parkinson's disease)"
"Place of Death: All"
"Race: All"
"States: All"
"Ten-Year Age Groups: All"
"UCD - ICD-10 Codes: All"
"Urbanization: All"
"Weekday: All"
"Year/Month: All"
"Group By: Month"
"Show Totals: True"
"Show Zero Values: False"
"Show Suppressed: False"
"Calculate Rates Per: 100,000"
"Rate Options: Default intercensal populations for years 2001-2009 (except Infant Age Groups)"
"---"
"Help: See http://wonder.cdc.gov/wonder/help/mcd.html for more information."
"---"
"Query Date: Mar 25, 2013 11:45:47 PM"
"---"
"Suggested Citation: Centers for Disease Control and Prevention , National Center for Health Statistics. Multiple Cause of Death"
"1999-2010 on CDC WONDER Online Database, released 2012. Data are from the Multiple Cause of Death Files, 1999-2010, as compiled"
"from data provided by the 57 vital statistics jurisdictions through the Vital Statistics Cooperative Program. Accessed at"
"http://wonder.cdc.gov/mcd-icd10.html on Mar 25, 2013 11:45:47 PM"
"---"

John