EPID 503 – Class 6 Standardization

Last Class: Total Mortality Rate # people who became newly dead (in some time and place) # people in population Same as incidence but all people at risk *On the population-level, often prevalent disease is assumed to be so rare that total population ~ population at risk for incidence estimation *Learned that for cervical cancer, this was not the case

Last Class: Total Mortality Rate # people who became newly dead (in some time and place) # people in population Rate vs. proportion (ie. risk): On the population-level, we cannot tally person-time, so these “rates” on the large scale are assumed to occur in one year to make people*1 year or person years Estimated with mid-point population to get best estimate of average population size during time period

Today We Discuss Age Standardization What’s the issue?

What we really want to know is – Is a person more likely to die if they were a member of population A as compared to population B?

Even with the same age-specific rates, a population that is younger will appear to have lower overall mortality rates.

Unadjusted May Be Good for Funeral Director but Problematic for Public Health While unadjusted rates may be useful if you run a funeral home, we can’t conclude that one population is healthier, at less risk, etc. than another without making them more comparable.

To Compare Across Populations We Need Comparable Groups Method 1 asks “How would the rates of death compare in two populations if they had the same age distribution?” What is this method called? When is it most useful? While unadjusted rates may be useful if you run a funeral home, we can’t conclude that one population is healthier, at less risk, etc. than another without making them more comparable.

Direct Standardization Explained Age-Specific Rates from Population A Age-Specific Rates from Population B Because using age-specific death rates from populations typically only used in large groups Applied to The age distribution of a standard population (eg. US population in 2000) Note: Standard population is somewhat arbitrary

How to Implement the Direct Method For each population: Calculate age-specific rates Multiply age-specific rates by the # of people in corresponding age range in standard population (generates the expected deaths in each age group of the standard population if they had the rates of your population) Sum the expected # of deaths across all age groups (generates the total expected deaths in the standard population if they had the rates of your population) Divide total # of expected deaths by total standard population (generates the mortality rate in standard population if they had the rates of your population ) Result: Age-adjusted mortality rate for your population that can now be compared to crude from standard or other similarly standardized rates

To Compare Across Populations We Need Comparable Groups Method 2 asks “How many deaths would I have expected if this population had the same mortality rates as some standard population (e.g. the US)?” What is this method called? When do we pick this method? While unadjusted rates may be useful if you run a funeral home, we can’t conclude that one population is healthier, at less risk, etc. than another without making them more comparable.

Indirect Method of Standardization Rates from the Standard population Useful when I don’t have or trust the group-specific rates (i.e. population is too small) Applied to the age distribution of the study population

How to Implement the Indirect Method Acquire age-specific mortality rates for standard population Multiply standard population’s age-specific rates by # of people in age range in study population (generates the expected number of deaths in your population if it had the mortality rate of the standard) Sum expected # of deaths across age groups in study population (generates the total number of expected deaths in your population if it had the mortality rates of the standard) Divide observed # of deaths by expected # of deaths in study population (observed/expected) Result: SMR (>1 more than expected, =1 as expected, <1 less than expected)

Let’s Look at Populations with the Same Age-Specific Rates but with Different Ages Young 0.002 1000 Middle 0.005 500 Old 0.010 200 Total 1700 Rate N Young 0.002 200 Middle 0.005 500 Old 0.010 1000 Total 1700

With this Distribution, Let’s Estimate the Crude Rates that Would be Observed Expected Deaths Young 0.002 1000 1000*0.002 = 2 Middle 0.005 500 500*0.005 = 2.5 Old 0.010 200 200*0.01 = 2 Total 1700 6.5 6.5/1700=0.0038 Rate N Expected Deaths Young 0.002 200 200*0.002 = 0.4 Middle 0.005 500 500*0.005 = 2.5 Old 0.010 1000 1000*0.01 = 10 Total 1700 12.9 12.9/1700=0.0076

Mathematically It’s a Weighted Average 0.002*1700 + 0.005*0 + 0.01*0 = 17000 0.002* (1700/1700) + 0.005*(0/1700) + 0.01* (0/1700) = 0.002*1 + 0.005*0 + 0.01*0 = 0.002 We’re basically just shifting the overall rate to more closely resemble the rates in the groups with the most number of people Rate N Young 0.002 1700 Middle 0.005 Old 0.010

Summary of Direct and Indirect Adjustment Population Structure Age-specific death Rates Direct Standard Observed Indirect