Fe 10 Standardization

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Direct standardization

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- Direct standardisation uses the observed age-specific rates of death or disease in a study population and applies them to a standard population of known age distribution. Then we can calculate an age-adjusted summary rate for each study population.
1. take age-specific rates for all the populations under study (or enough data to calculate them)
2. multiply by the appropriate standard population with a known age distribution

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Indierect standardization

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we can calculate the number of deaths that would be expected if both populations had the same (standard) age-specific death rates, but kept their real age structure
. Take the number of people in each age group of the study (Ecuadorian) population
2. Multiply it by the corresponding age-specific mortality rate in the standard (Swedish) population.
3. Calculate the ratio of total observed deaths to total expected deaths for this example is:

The ratio of the number of deaths observed in the study group or population to the number that would be expected if the study population had the same specific rates as the standard population. Usually expressed as a percentage.
Ex. So the SMR for Ecuador in this example is 152%.

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What information do I need for calculating indirect standardization

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1. the age specific mortality rates of a standard population
2. age structure of the study population
3. the total number of deaths or disease of the study population

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how do you calculate CMF vs SMR

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Comparative Mortality Figure - an age-standardised rate ratio by dividing the age-adjusted rate of one study population against the other.

SMR = divide observed mortality rates by expected deaths that were calculated

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When is best to use one over the other

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1. Summary measures are not good when there is large differences in rates between different group ages. This is masked in the summary measure
2. indirect sta. is better when there is a small number of cases (like rare cancer) bc rates/mortality rates via direct standarization would be subject to sampling variability