1 A history of life and death in Australasia and Pacific: What is life expectancy? Tony Blakely AEA Masterclass Burden of Disease Epidemiology, Equity and Cost-Effectiveness Programme
Consider New Zealand women. What is Their life expectancy? The age which 50% of the population will live to? The commonest age at death?
4 What is life expectancy? Two types: Period (most common) and cohort Period: Take mortality rates at given time (e.g. 1901) Walk a synthetic cohort (100,000 by convention) through these age-specific mortality rates till they are all dead Calculate the average number of years lived (or the area under survival curve, divided by 100,000) Cohort: Take people born at a given time (e.g.1901) Calculate actual average number of years lived using this cohorts actual mortality rates by year post-birth
Lifetable 1901 non-māori female (period) Exact age (years) Out of 100,000 females born Number alive at exact age Average Number number dying in the alive in the age interval age interval Probability that a female who reaches this age Lives another year Dies within a year Central death rate for the age interval Expected number of years of life remaining at age x x l x L x d x p x q x m x e x 0 100,000 94,480 8,675 0.9274 0.0726 0.0753 56.8 1 91,325 90,452 1,746 0.9809 0.0191 0.0193 61.2 2 89,579 88,915 1,328 0.9852 0.0148 0.0149 61.4 90,452 = 91,325 1,746/2 0.0191 = 1,746/91,325 0.0191 = -ln(0.9809) =sum Lx / 91,325 3 88,251 87,787 928 0.9895 0.0105 0.0106 61.3 4 87,323 87,053 540 0.9938 0.0062 0.0062 60.9 5 86,783 86,703 159 0.9982 0.0018 0.0018 60.3 95 229 173 112 0.5119 0.4881 0.6697 1.4 96 117 86 62 0.4690 0.5310 0.7572 1.3 97 55 39 32 0.4242 0.5758 0.8574 1.1 98 23 16 14 0.3782 0.6218 0.9723 1.0 99 9 6 6 0.3315 0.6685 1.1041 0.9 100 3 2 2 0.2849 0.7151 1.2555 0.6
Survival curves 1901 non-māori, period and cohort
Frequency of death by age, period 1901 & 2011
9 A history of life and death in Australasia and Pacific: New Zealand, WWII to present Tony Blakely AEA Masterclass Burden of Disease Epidemiology, Equity and Cost-Effectiveness Programme
Māori and non-māori LE to 2010-12
11 Explanations and projections Explanations: Age Cause of death Risk factors Societal Projections
Contribution to LE by age 0-1 yr, 1-14 yr 65+ yr 65-84, 85+ yr
Older (NCD) mortality turned c.1970 (period effect)
Disease specific mortality over time Source: Ministry of Health (2014). Historic mortality rates, 1948-2010.
Age-standardised rates per 100,000 Age-standardised rates per 100,000 Age-standardised rates per 100,000 Age-standardised rates per 100,000 Cancer incidence different diseases with different trends 120 100 80 Lung Colorectal Prostate (excl PSA effect) Melanoma Males 140 120 100 Breast Colorectal Melanoma Lung Females 80 60 60 40 40 20 20 0 1956 1966 1976 1986 1996 2006 2016 Year 30 Stomach Brain Leukaemia NHL 25 Kidney Pancreatic Myeloma 0 1956 1966 1976 1986 1996 2006 2016 Year 25 Cervical Ovarian Stomach Leukaemia Pancreatic NHL Brain Kidney Myeloma 20 20 15 15 10 10 5 5 0 1956 1966 1976 1986 1996 2006 2016 Year 0 1956 1966 1976 1986 1996 2006 2016 Year
Breast cancer incidence rates by ethnicity Suggestion survival gaps widening faster than incidence gaps Breast cancer mortality rates by ethnicity NZCMS and CancerTrends (Incidence) findings 16
Tobacco
Tobacco ever smoking by cohort by sex/ethnicity
Alcohol New Zealand middle of the pack
Fat, energy, BMI
Social determinants Complex not always what simple theory suggests Urbanisation on net beneficial for Māori Almost inescapable that structural reforms of 1980s-90s differentially and adversely impacted Māori (especially through unemployment) No correlation of GDP increase with LE increase within NZ over time, and indeed improving income (individuallevel) and GDP (country-level) have both positive and negative effects. Indeed, some of periods of strongest increase in LE have happened in recessions Health care increasingly important (e.g. CVD, cancer)
Unemployment one social determinant
Looking forward: cohort LE 65 if 1.5% mortality continues Superannuation age has to go up, guarding against inequalities Public health needs to think more about morbidity and productivity near retirement age
Looking forward Further LE increase inevitable There must be biological limits what are they? Basal rate of cell mutation in clean environment? Should future health research & policy focus on: Separate diseases (what we do now)? The aging process itself? Public health needs to concern itself: Less with LE gain as the goal in and of itself More on morbidity, equity, and social and environmental sustainability