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Statistics Proves Smoking Is Unhealthy

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Just after World War II, Richard Doll and Bradford Hill of the Statistical Research Unit of the Medical Research Council decided to study the alarming increase in cases of lung cancer occurring in Great Britain.

They had two theories for the extra cases: increased air pollution and increased use of tar in paving roads. They interviewed lung cancer patients in 20 London hospitals and other patients of similar age and sex in the same hospitals.

It turned out that exposure to pollution and tar was comparable in the two groups, but only 7% of nonsmokers were in the lung cancer group. The results convinced Doll to quit smoking.

Others were not convinced, so Doll and Hill sent letters to 59,000 British medical doctors asking about their smoking habits and if they would agree to be followed for health effects over time. About 40,000 replied, and in the next three years, 36 of the smokers died from lung cancer compared with 0 of the nonsmokers. The results convinced Hill to quit smoking, but others still were not convinced and more studies were completed. These pioneering studies exhibited all the hallmarks of causation:

  • Development of disease a reasonable time after starting to smoke
  • Higher probability of disease with more cigarettes smoked
  • A strong relationship unlikely to occur by chance
  • A consistent effect across different populations and circumstances

Today, this causal relationship is no longer in doubt, as key biological mechanisms underlying the disease-causing effects of smoking have been thoroughly proven in statistically designed laboratory experiments.

Without statistics, the strength of the evidence could not be evaluated and we wouldn’t know that smoking is bad for you.


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