Data Studio

MSOB x393

DATE: March 14, 2018
TIME: 1:30 - 3:00 pm
TITLE: Autism Trend in True Case Prevalence in California 1980-2017 via Time Series Analysis
Alexander MacInnis, Lorene Nelson, Kristin Sainani, Health Research and Policy (Epidemiology)



Estimates of autism prevalence have increased exponentially over the past few decades, yet it is unknown how much of this increase reflects an increase in true case prevalence and how much is due to other factors, including diagnostic practice and such.  An increase in true case prevalence would imply an increasing effect of environmental factors rather than genetic factors.  We have data showing the incidence of initial diagnosis of autism by diagnostic year, birth year and sex in California 1980-2017.  Survival analysis methods enable us to estimate the parameters of a model of the birth year trend in true case prevalence, correcting for both diagnostic year and age effects.  We will discuss alternative models as well as alternative numerical fitting schemes.

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Background readings:

A MacInnis. Autism Prevalence Trends by Birth Year and Diagnostic Year: Indicators of Etiologic and Non-Etiologic Factors - an Age Period Cohort Problem. Stanford University Thesis 2017;