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Topic 5: Rates and Standardization Modified from the notes of A. Kuk P&G pp. 66—95
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Demographic Data Size of population and its composition by gender, race, age etc
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Vital Statistics Vita --- life Tell a story of life with numbers so that vital services can be provided --- food, lodgings, health, water, etc
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Births Natural Increases Marriages Divorces Diseases Deaths Complex and massive story because we often need to deal with whole countries.
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Describe health status of a population Spot trend Make projections Planning Set policy Compare groups Want to be able to:
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Provisional statistics USA 12 months ending in April (millions)199319941995 Live births4.0754.0173.966 Deaths2.2072.2802.297 Increase1.8681.7371.669 Marriages2.3522.3302.345 Divorces1.2031.1851.179 Infant deaths * 33,70032,40031,100
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Death rate increasing?
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“Crude” rate, single number, summary allows for standardization makes comparisons more meaningful
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State of Massachusetts in 1992Number Population 6,060,943 Live births87,202 Deaths: Total53,804 Under 1 year569 Crude birth rate per 1000 persons per year Crude death rate per 1000 persons per year Infant mortality rate per 1000 live births per yr
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Rate a Per 1,000199319941995 Live births15.915.515.2 Fertility rate b 69.067.966.8 Deaths8.68.8 Increase7.36.76.4 Marriages9.29.0 Divorces4.74.64.5 Infant deaths c 8.38.27.9 a=pop., b=women 15-44, c=live births
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Crude rate answer all questions? StatusPop n Impair’sRate /100,000 Employed98,9175525.58 Unemployed7,462273.62 Not in labor force 56,7783686.48 Total163,1579475.80
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Therefore it is better to be “employed” than “not in the labor force” as far as hearing is concerned Confounders?
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Age distribution EmployedNot in labor force AgePop n PercentPopnPercent 17-4467,98768.720,76036.6 45-6427,59227.915,10826.6 65+3,3383.420,91036.8 Total98,917100.056,778100.0
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Age Composition of Population Age Pop n ImpairsRate /1000 17-4494,9304414.65 45-6443,8573087.02 65+24,3701988.12 Total163,1579475.80
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Age Specific Impairment Rates Currently employed Age Pop n ImpairsRate /1000 17-4467,9873465.09 45-6427,5921796.49 65+3,338278.09 Total98,9175525.58
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Age Specific Impairment Rates Not in labor force Age Pop n ImpairsRate /1000 17-4420,760803.85 45-6415,1081177.74 65+20,9101718.18 Total56,7783686.48
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Age Specific Impairment Rates Age Employed /1000 Not in labor force /1000 17-445.093.85 45-646.497.74 65+8.098.18 Total5.586.48
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Can we capture what is happening with a single number? Problem caused by different age profiles. Standardize Direct Indirect (skipped)
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Direct method of getting rid of age confounder is to standardize the age distribution and apply the appropriate age specific rates. Select a standard age distribution. Logical choice is the total population
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For Currently Employed Age Pop n Rate /1000 Expected Impairs 17-4494,9305.09483.2 45-6443,8576.49284.6 65+24,3708.09197.2 Total163,157965.0
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For those not in labor force Age Pop n Rate /1000 Expected Impairs 17-4494,9303.85365.5 45-6443,8577.74339.5 65+24,3708.18199.3 Total163,157904.3
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Crude rate Not in labor force > Employed Age adjusted Not in labor force < Employed Remember 1.This is a construct. 2.Choice of standard distribution is arbitrary.
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Age-Adjusted Cancer Death Rates, Males by Site, US, 1930-1996 Adjusted using the U.S. population in 1940 as the standard distribution
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Age-Adjusted Cancer Death Rates, Females by Site, US, 1930-1996
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When to use adjustment: Check that the age-specific rates follow more or less the same trend for all the populations to be compared. Is there a confounder? Age? Sex?
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go so no
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