false

Class Notes
(834,991)

Canada
(508,850)

University of Toronto St. George
(43,993)

TRN125Y1
(30)

Caroline Barakat
(13)

Lecture

by
OneClass9488

Unlock Document

Trinity College Courses

TRN125Y1

Caroline Barakat

Fall

Description

C07 11: Demographic and Epidemiologic Transitions in Population Health
Date: Nov 28, 2012
Slide 2: Lecture Outline
Life Expectancy (LE) and longevity
o Positive health outcomes today
Survival probability curve
o What does it mean?
Gain in life expectancy
Active LE
o Actual LE vs. active LE
Aging and longevity
o Video refers to the area with the highest # of centenarians living there
Slide 3: Life Expectancy (LE)
Average lifespan of a cohort of individuals observed after an inception of time
Not really looking at how long each person is going to live; looking @ a collection of individuals
who are observed after some point in time (inception time) – could be different – so can look @
life expectancy of ppl living with cancer, life expectancy after certain treatment, general life
expectancy after birth
o There are diff inception times: birth, onset/diagnosis of certain disease/diff types of
cancer, initiation of treatment
From theoretical perspective, calculating life expectancy involves observations in which all
members of a certain cohort have died – that’s the only way you can know how much time they
have contributed – average life expectancy
Total amount of time that ppl in cohort lived and then dividing by the # of individuals at the
inception point
o Formula = simple – average
o How many months/years every cohort member has lived summed/# of cohort members
Slide 4: Calculate life expectancy
Graph shows: months since inception point (diagnosis or treatment – not general @ birth life
expectancy because ppl longer than just months)
Life expectancy = 130/10 = 13 months
o So, follow cohort until they die and add up what the contributed divided by the # of
members in cohort
LE = Total time/# of individuals in a cohort
Graph shows horizontal life spans for each individual (in months)
But usually, when we have a large # of individuals we look at it as vertical cohort
memberships/bars
o So, in terms of how many individuals contributed 1 month, how many individuals
contributed 2 months etc;
o When looking @ vertical bars, as members of the cohort die, the vertical bars shrink in
size
1 C07 11: Demographic and Epidemiologic Transitions in Population Health
Date: Nov 28, 2012
o At inception point, right @ zero, we had 684 cohort members
They all contributed one month and up to 6 months, beyond that, ppl started
dying – so have vertical bars that give an indication of how many individuals
contributed to the life expectancy and because you have large # of individuals –
can’t have horizontal bars – use vertical bars instead
Slide 5:
What represents the total number of life-months experienced by the cohort?
o N=684
What gives an indication of life expectancy/total contribution of each of those cases?
o Integration – area under the curve
o Larger the area – have big contribution – that’s the total # of months; less area = less
months contributing – then you still have to divide it by 684
o Area under curve = total # of months all individuals in the cohort contributed in terms of
survival
LE = area under the curve/684
o Area under the curve aka survival curve because gives indication of how many ppl
survive beyond a certain month
You are told that area = 8236
Tied into the concept of survival curve is the concept of survival probability curve
Slide 6: The Survival Probability Curve
Proportion of a population living after inception point
Y-axis here is no longer the # of cases but rather you have a scale of 0-1
o At 0 point, everyone survives
o Reason why it’s called survival probability curve is because now you have y-axis on
probability scale 0-1
o How many ppl will survive til 20 months?
Go 2 20 months – see that there’s 20% survival of 20 months
Survival vs probability to which ppl live to certaintime
o Gives indication of proportion of a population living after a given age/treatment etc;
o How much time a person survives after an inception point versus what is the survival
rate
Main difference btn survival curve and survival probability curve is the latter is on a probability
scale of 0-1 whereas the former gives indication of how many individuals are part of the cohort
and then the total amount of time that they all contributed to LE
Slide 7: Gain in life expectancy
Usually used when there’s an association or one wants to associate with one health strategy
over another so that you can see what works better for those individuals
You have time since inception and then you have 2 scenarios:
2 C07 11: Demographic and Epidemiologic Transitions in Population Health
Date: Nov 28, 2012
o Treatment and control
o Or maybe two treatments
You’re following the cohort again (same as b4) – build survival curve first and then build survival
probability curve
o This gives an indication of those 2 curves
o Control has lighter shade of grey survival probability curve whereas the treatment =
darker shade
o Can determine if someone should go for that particular treatment – can see that it has
some effect over the control; has been shifted to the right
o Benefit of the treatment is the difference – it is the area in the middle which is referred
to as delta LE (aka the change in LE)
o So, the difference in benefit = the area between those 2 curves which represents
whatever life expectancy was after treatment minus that of control
o Is it beneficial for the treatment to be given? Look @ area between the 2 curves
Slide 8: Active life expectancy
Not looking at mortality or morbidity – looking @ healthy measures – how long ppl would live
but also looking @ good quality of life
Proportion of total life expectancy to be lived without chronic disability (not going thru disability
that doesn’t allow you to live an active life)
Graph: UN 2007, World population prospects
o Gives indication of active life expectancy and life expectancy for 3 diff time periods
(1935, 1999, 2008)
o First one is solid bar – active life expectancy in 1935 vs another line for LE for 1935 –
that difference = amount of time that’s contributing to LE (=living with disability; it is not
active life expectancy)
o Same thing again: active LE in 1999 and total LE in 1999 – also see a gap – gap is
attributed to many things: difference between active life expectancy and actual life
expectancy = ppl are living longer but necessarily without disability – so older ppl aren’t
living active lifestyle but they’re also living longer – pushes LE over and above but not
active life expectancy
o Implication is that by 2080 – we have changing trend of increased LE and also hoping
that there’s smaller gap between active LE and LE
o This is all very relevant for countries looking @ retirement options, increasing
retirement rate – ensure balance in society
European – retirement rate from 65 to 67 to achieve balance
Slide 9: Demography of Aging

More
Less
Related notes for TRN125Y1

Join OneClass

Access over 10 million pages of study

documents for 1.3 million courses.

Sign up

Join to view

Continue

Continue
OR

By registering, I agree to the
Terms
and
Privacy Policies

Already have an account?
Log in

Just a few more details

So we can recommend you notes for your school.

Reset Password

Please enter below the email address you registered with and we will send you a link to reset your password.