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Human Life Tables and Survivorship Curves

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PURPOSE: Test hypotheses about human survivorship using: 1.Life tables 2. life expectancy 3.Survivorship curves

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Hypotheses about Males and Females R.I.P. BRB – HO: The life expectancy of women is the same as for men or less than that of men. – HA: Women have a greater life expectancy than men.

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Hypotheses about Males and Females R.I.P. BRB – HO: Men do not have a greater life expectancy during child bearing years. – HA: Men have a greater life expectancy than women during child bearing years.

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Hypotheses about Public Health R.I.P. BRB – HO: Human life expectancy has not increased over the period of time during which people were buried in our study area cemeteries. – HA: Human life expectancy has increased over this time period

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What are life tables? A life table contains age-specific survival and mortality rates in a population. It also contains fecundity and age distribution information. Life tables come in 2 varieties: – Cohort life table: Follows a group of individuals born at the same time. – Static life table: Constructed by recording the age at death of a large number of individuals. This is what well be making.

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Life Tables Age Class x dxdx nxnx lxlx axax x Etc. X = a reference number we assigned to refer to the different classes

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Life Tables Age Class x dxdx nxnx lxlx axax 0-51x x Etc. X = a reference number we assigned to refer to the different classes

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Life Tables Age Class x dxdx nxnx lxlx axax x x+1 Etc. X = a reference number we assigned to refer to the different classes

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Life Tables Age Class x dxdx nxnx lxlx axax Etc. d x = the number of individuals that die in the x age class.

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Life Tables Age Class xdxdx nxnx lxlx axax How many? Etc. n x = total number of individuals surviving to the x age class. n x = n x-1 - d x-1

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Life Tables Age Class xdxdx nxnx lxlx axax How many? Etc. n x = total number of individuals surviving to the x age class. n x = n x-1 - d x-1

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Life Tables Age Class xdxdx nxnx lxlx axax qxqx l x = Etc. (l x ) Survivorship: Portion of population that survived to the x age class

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Life Tables Age Class xdxdx nxnx lxlx axax qxqx l x = Etc. (l x ) Survivorship: Portion of population that survived to the x age class

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Life Tables Age Class xdxdx nxnx lxlx axax qxqx a x = Etc. a x = Given you reach the x age class, what is the probability you live to the NEXT age class.

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Life Tables Age Class xdxdx nxnx lxlx axax qxqx = 94/ a x = Etc. a x = Given you reach the x age class, what is the probability you live to the NEXT age class.

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Life Tables Age Class xdxdx nxnx lxlx axax qxqx q x = Etc. q x = Given you reach the x age class, what is the probability you do NOT live to the NEXT age class.

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Life Tables Age Class xdxdx nxnx lxlx axax qxqx Etc. a x + q x = 1

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Life Tables Age Class xdxdx nxnx lxlx axax qxqx Etc. a x + q x = 1 Make three: Males, Females, and Totals for your groups data

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x Dx Nx lx ax qx 1000lx log1000lx Example Life Table

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Life Expectancy The amount of time one is expected to live once age class x is reached or during a specified period of time. How can we test whether health issues influence survivorship, or if there is a difference between males and females?

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Use your lab sections data: Compute life expectancies for all age groups and for childbearing years. Do this for Males, Females, and Totals Compute life expectancies for the older cemetery and the younger cemetery. You will have 8 life e x values

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Survivorship curves: R.I.P. BRB Make 2: your data (Male vs. Female) Make 2: your data (Male vs. Female) previous data (Old vs. New)

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Chi Square tests How do we know if 2 survivorship curves differ? 1) look at the graphs 2) do a 2 test Well use Females as our observed group and males plus females/2 as expected. Old vs. new

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Graph dx for males vs. females and old vs. new. What does this tell us?

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A lot of data… To leave today you need 1) Three life tables (male, female, all) using lab sections data 2) Eight life expectancies 3) Survivorship curve (M and F) (lab section data) 4) Survivorship curve (Old and New) (Previous Data) 5) dx graphs 6) Two Chi square tests: Old vs. New (Previous data), M vs. F (lab sections data)

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