Statistical Methods and Analysis of Environmental Health Data

The following was written by SukhDev Mishra,Ph.D., Division of Bio-Statistics, National Institute of Occupational Health, Indian Council of Medical Research, Ahmedabad(India)

group shot

Statistical Methods and Analysis of Environmental Health Data Workshop group.

I was fortunate to attend the SAMSI workshop on Statistical Methods and Analysis of Environmental Health Data last week in Mumbai. It focused on various topics related to the statistical analysis of environmental health data, some of which discussed latest methodological development in this field, particularly during the first day’s opening lecture from Professor Joel Schwartz.

Time series data has proven to be critical in the assessment of systematic impact of environmental factors on human health. Professor Francesca Dominici, a researcher with significant contributions in this area was a very dynamic and enthusiastic co-leader for this workshop. She discussed in length the statistical principles and assumptions of multi-site time series analysis along with careful interpretation of such data. Due to technological advances and regular measurement availability, time series data could be accessed and easily analyzed with the techniques elaborated by Professor Dominici, which will be integral to the success of my future studies.

Working Group 5 - Gene x Environment Interactions

Working Group 5 – Gene x Environment Interactions

The Gene x Environment Analysis & Epigenetics lecture taken by Professor Bhramar Mukherjee provided very useful information on interaction/additive and multiplicative models citing practical applications in area of environmental health that she developed. Her very creative way of teaching, blended with great sense of humor, kept us engaged so much so that we wouldn’t blink for a second.

Spatial statistics is a critical part for environmental health data, so it was helpful to have the basics covered by Dr. Safraj Shahul Hameed and Dr. Brian Reich well. Professor Donna Spiegelman presented a wonderful talk on measurement error starting from statistical notations to complete logit function (being a statistician ….I always love this part J ). She put great effort explaining Regression calibration method for MS/EVS and algorithms. Interesting talk!

Working groups were engaged in different exercises that included working on different problems/real data sets generated through various participants and coming up with new analysis and interpretation of data. I worked on Exposure Modelling of Ambient and Household Air Pollution for Acute and Chronic Health Effects. I enjoyed working with my fellow WG colleagues- Kalpana Balakrishnan, Santu Ghosh, Donna Spiegelman, Kevin Lane, Joel Schwartz, Sourangsu Chowdhury , and Poonam Rathi. Fine scientific arguments during the process of analysis were the crux of our exercise; thanks to Joel, Kalpana, Donna and Kevin especially.

This is no way a comprehensive description of this workshop, just my thoughts. I would also like to record here that I learned from each and every speaker and fellow participant. It was a gathering of great scientific minds and very inquisitive researchers. My understanding is that one of SAMSI’s objectives is to foster a culture of collaborative research among Indo-US researcher in area of public health; and I could see that coming true as we collectively discussed ideas on how to continue our work in mutual scientific engagement. I hope these efforts result in great scientific endeavors in coming time for environmental health priorities.

People drinking tea during a break

Enjoying afternoon tea.

One of the unique features of this workshop was meticulous planning by the team of organizers, be it scientific contents or overall execution by Professor Richard Smith, Professor Sujit Ghosh, Professor Francesca Dominici, and Ms. Krista Coleman whose scientific management and interaction with participants was very encouraging.

My working experience mainly includes working in pharmaceutical industry earlier, as biostatistician, and I consider myself a beginner in environmental health. This workshop has helped me to gain more scientific perspectives in this area by leaps and bounds.

This kind of knowledge sharing exercises may prove very helpful for researchers in the area of statistics and epidemiology to address India’s most pressing public health needs. Thank you SAMSI, Harvard, ISI-Kolkata and all of the other participating organizations for such a wonderful experience!

 

 

Advertisements

2 thoughts on “Statistical Methods and Analysis of Environmental Health Data

  1. Many congratulation everyone! What a great Theme and team too.
    I was looking for such a great workshop from last couple of years and unfortunately this I was unable to attend. I really get some feeling based on integration of different research area air pollution to genetics. (currently finalising my PhD research in environmental epidemiology specific focus on weather and mortality in rural India at Umea university, Sweden) I am looking forward to participate in such worksop in near future.

  2. Very well written and informative article. Sophisticated application of Statistics can play important role and is indispensable for environmental health research like it has been proven in other field of scientific research. Great to see that such eminent statisticians from the globe have been gathered to discuss application of statistics in environmental health research. Look forward to see more such engagements and hope this will help to drive environmental health research in productive direction where this branch of science meets the need of hour and demand of mankind.

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s