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Case Study for air pollution in RR
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---
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title : Reproducible Research Case Study
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subtitle : Identifying Harmful Constituents in Particulate Matter Air Pollution
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author : Roger D. Peng, Associate Professor of Biostatistics
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job : Johns Hopkins Bloomberg School of Public Health
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logo : bloomberg_shield.png
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framework : io2012 # {io2012, html5slides, shower, dzslides, ...}
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highlighter : highlight.js # {highlight.js, prettify, highlight}
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hitheme : tomorrow #
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url:
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lib: ../../libraries
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assets: ../../assets
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widgets : [mathjax] # {mathjax, quiz, bootstrap}
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mode : selfcontained # {standalone, draft}
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---
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## What Causes PM to be Toxic?
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- PM is composed of many different chemical elements
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- Some components of PM may be more harmful than others
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- Some sources of PM may be more dangerous than others
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- Identifying harmful chemical constituents may lead us to strategies
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for controlling sources of PM
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---
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## NMMAPS
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- The National Morbidity, Mortality, and Air Pollution Study (NMMAPS)
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was a national study of the short-term health effects of ambient air
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pollution
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- Focused primarily on particulate matter ($PM_{10}$) and ozone ($O_3$)
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- Health outcomes included mortality from all causes and
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hospitalizations for cardiovascular and respiratory diseases
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- Key publications
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- http://www.ncbi.nlm.nih.gov/pubmed/11098531
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- http://www.ncbi.nlm.nih.gov/pubmed/11354823
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- Funded by the [Health Effects
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Institute](http://www.healtheffects.org)
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- Roger Peng currently serves on the Health Effects Institute Health
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Review Committee
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---
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## NMMAPS and Reproducibility
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- Data made available at the Internet-based Health and Air Pollution
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Surveillance System (<http://www.ihapss.jhsph.edu>)
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- Research results and software also available at iHAPSS
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- Many studies (over 67 published) have been conducted based on the
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public data <http://www.ncbi.nlm.nih.gov/pubmed/22475833>
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- Has served as an important test bed for methodological development
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---
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## What Causes Particulate Matter to be Toxic?
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<img src="lippmann.png" width=1000 />
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<http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1665439/>
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- Lippmann *et al.* found strong evidence that Ni modified the
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short-term effect of $PM_{10}$ across 60 US communities
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- No other PM chemical constituent seemed to have the same modifying
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effect
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- To simple to be true?
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---
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## A Reanalysis of the Lippmann *et al.* Study
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<img src="dominici.png" width=1000 />
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<http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2137127/>
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- Reexamine the data from NMMAPS and link with PM chemical constituent
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data
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- Are the findings sensitive to levels of Nickel in New York City?
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---
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## Does Nickel Make PM Toxic?
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<img src="nickel-beta.png", height=400>
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- Long-term average nickel concentrations appear correlated with PM risk
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- There appear to be some outliers on the right-hand side (New York City)
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---
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## Does Nickel Make PM Toxic?
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<img src="nickel-beta-lm.png", height=450>
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- Regression line statistically significant ($p < 0.01$)
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---
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## Does Nickel Make PM Toxic?
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<img src="nickel-beta-lm-no-ny.png", height=450>
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- Adjusted regression line (blue) no longer statistically significant
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($p < 0.31$)
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---
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## Does Nickel Make PM Toxic?
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<img src="ni-leaveout.png" height=500>
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---
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## What Have We Learned?
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- New York does have very high levels of nickel and vanadium, much
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higher than any other US community
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- There is evidence of a positive relationship between Ni
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concentrations and $PM_{10}$ risk
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- The strength of this relationship is highly sensitive to the
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observations from New York City
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- Most of the information in the data is derived from just 3 observations
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---
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## Lessons Learned
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- Reproducibility of NMMAPS allowed for a secondary analysis (and
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linking with PM chemical constituent data) investigating a novel
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hypothesis (Lippmann *et al.*)
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- Reproducibility also allowed for a critique of that new analysis
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and some additional new analysis (Dominici *et al.*)
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- Original hypothesis not necessarily invalidated, but evidence not as
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strong as originally suggested (more work should be done)
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- Reproducibility allows for the scientific discussion to occur in a
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timely and informed manner
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- This is how science works
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