230984 Understanding the autism epidemic: Data and dogma

Tuesday, November 9, 2010 : 4:50 PM - 5:10 PM

Craig J. Newschaffer, PhD, MS , Department of Epidemiology and Biostatistics, Drexel University School of Public Health, Philadelphia, PA
     
This presentation will review statistics on secular trends in autism risk over the past two decades. It will highlight challenges to developing evidence supporting or refuting hypotheses related to changing autism risk in the population. Issues pertinent to the construction of informative measures of disease frequency for this condition will be highlighted. Discussion of how messages relaying statistical information on autism incidences have been communicated to professional and lay audiences have been communicated will also be included.

Learning Areas:
Biostatistics, economics
Public health or related public policy

Learning Objectives:
1. Discuss statistics on secular trends in autism risk over the past two decades. 2. Evaluate challenges to developing evidence supporting or refuting hypotheses related to changing autism risk in the population. 3. List issues pertinent to the construction of informative measures of disease frequency for this condition. 4. Discuss how messages relaying statistical information on autism incidences have been communicated to professional and lay audiences.

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I am qualified to present because I am Professor and Chairman of the Department of Epidemiology and Biostatistics at Drexel. I now now lead an NIH Autism Center of Excellence project studying a large cohort of mothers of children with autism at the start of subsequent pregnancies.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.

Back to: 4390.0: Annual Special Session: Controversies in Public Health due to Misinterpretation of Statistical Information