"The whole aim of practical politics is to keep the populace alarmed (and hence clamorous to be led to safety) by menacing it with an endless series of hobgoblins, all of them imaginary." H. L. Mencken.
And here’s an example. For decades we’ve heard about the deaths. The only problem is that the peak doesn’t peak. This reminds me of an official analysis in the 1970s concerning x heroin addicts having to steal y dollars per day for 365 days in the year. The total amount stolen, by this calculation, was several times more than the total amount stolen in reality.
The following quotes are from this article.
“Where are the bodies?
Models that predict thousands of smog-related
hospitalizations in Toronto don’t hold up
We found no evidence that increased smog led to more hospital visits
For many years we have heard that air pollution in Canada is responsible for thousands of annual deaths and hospitalizations. In 2004 Toronto Public Health claimed that 1,700 premature deaths and 6,000 hospitalizations occur each year in Toronto alone, due to air pollution. The Ontario Medical Association, provincial and federal governments, lung associations and other groups regularly cite these kinds of figures in support of calls for new regulatory initiatives. These death and hospitalization rates are astonishing. It is like suffering a 9/11-sized terrorist attack every 10 months.
But is it really true? The estimates are derived by taking correlations in the epidemiological literature between observed pollution levels and health indicators, like hospital admission rates, and then extrapolating across populations to estimate how many deaths and illness diagnoses can, in theory, be attributed to pollution. In other words, the numbers come from statistical models, not from direct observations. (emphasis added). That means we need to pay close attention to how the statistical modeling is done.”
This is exactly like the Global Warming illusion. The bad news is always from the projected awfulness.
“A fourth weakness of the literature is that few studies control for important factors like smoking, income levels and weather. Some recent studies have added in socioeconomic covariates. After doing so, the apparent effect of pollution vanished.
What we did not find was any evidence that increases in air pollution levels are associated with increased rates of hospital admissions. We looked at the data every which way imaginable. If we were to cherry pick, by looking only at a sub-sample of the time or by picking just the right form of the model, we could find evidence that CO or nitrogen dioxide (NO2) have positive effects on lung disease, but those results do not get strong support in the data. The models that get consistent support either show no pollution effects or — paradoxically — negative effects. In other words, in some cases as air pollution rises, hospital admissions go down. As odd as that sounds, we are by no means the first to report negative coefficients in the literature. Nobody is trying to argue that air pollution is good for you: this is either just noise in the data, or it might be an effect from “averting” behaviour, where people who are susceptible to lung problems stay indoors on days with bad air quality.”
It’s sad because this was such a noble, useful and alarming hobgoblin.
Cheerio and ttfn,
Grant Coulson
Cui Bono–Cherchez les Contingencies
