No correlation/causation list would be complete without discussing parental concerns over vaccination safety, rooted in the idea, popularized by celebrities like Jenny McCarthy, that measles, mumps and rubella (MMR) vaccinations are causally linked to autism spectrum disorders. Despite the medical community debunking the 1998 Andrew Wakefield paper that inspired the idea, and despite subsequent studies showing no causal link, even with multiple vaccinations, some parents remain fearful of an autism connection or other vaccine-related dangers [sources: The Lancet; Park; Sifferlin; Szabo].
While it's true that no vaccine is 100 percent harmless, the belief in this causal link arises mainly from natural parental concern, burdened by confusion, fueled by anecdotal evidence and influenced by confirmation bias, or "if I hadn't believed it I wouldn't have seen it." Further fueling the confusion is the fact that parents and doctors tend to recognize autism symptoms late, around the ages that children receive many vaccinations. In actuality, autism onset is quite complex and follows more than one pattern. Indeed, studies now show that onset can begin as early as 6-12 months [sources: CDC; Johnson and Schultz; Mandell et al.; NIH; Ozonoff et al.].
It's no harmless misunderstanding. In 2011, Time magazine reported that 13 percent of parents skipped, delayed or split up their children's vaccinations; in some rural areas, that number shot up to between 20 and 50 percent. Meanwhile, 15 years after this panic began, medical centers reported outbreaks of whooping cough and measles. Whether that correspondence is coincidental, correlative or causal is well worth considering [sources: O'Connor; Park; Park].
Author's Note: 10 Correlations That Are Not Causations
As much as I abhor poor experimental design, blind reliance on statistics and sensationalistic science reporting, it's worth mentioning that strong correlations, while not alone sufficient to prove cause, often point to areas worth investigating. Clearly, by "correlations" I don't mean autocorrelations, confounding variables or other artifacts of bad design or poorly understood methodological requirements and constraints; nevertheless, maybe the Internet can lay off the "correlation does not imply causation" slogan for a bit, or at least grow a bit more selective in its application.
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