Class Notes (834,991)
TRN125Y1 (30)
Lecture

# HLTC07 - Lec 11 - Demographic and Epidemiological Transitions in Population Health (near-verbatim)

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Department
Trinity College Courses
Course
TRN125Y1
Professor
Caroline Barakat
Semester
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
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