PBL Workshops Flashcards
(40 cards)
Age standardisation: crude death rate
sum of all deaths/
total population/time
Age standardisation: age-specific death rate
no. of deaths for the age group/
pop size of age group/time
Age standardisation: expected deaths for age group
age specific death rate x
no of people in standard pop age group
Age standardisation: age-standardised death rate
sum of expected deaths/
standard pop/time
Treat of Waitangi: Languages
English and Maori
Treat of Waitangi: Which version sets precedence
Maori
Treat of Waitangi: Voluntary or involuntary
Voluntary
Treat of Waitangi: Maori population after signing
The proportion of Maori pop in NZ decreased rapidly after the signing of the Treaty
Treat of Waitangi: Hāpu
Most hāpu signed the Maori version of the Treaty
Is ethnicity always self-identified
Not always
In some cases, individuals (e.g. children) may not be able to identify it themselves
Ethnicity / race
Ethnicity is not the same as race
Newborn children and mother ethnicity
New born children don’t need to be recorded as same ethnicity as mother
How is consistency of ethnicity responses maintained
A standard ethnicity question is used for collecting ethnicity
Can ethnicity change over time
The ethnicity identified by individuals can be changed over time
Ethnicity coding: recording vs reporting
Must be recorded exactly how participants responded into a data warehouse
Can decide how to report individuals’ ethnicity
Main methods of reporting ethnicity
Prioritised output
Total response output
Sole/combination output
Ethnicity coding: different levels
Level 1: least detailed, 1 digit
Level 2: more detailed, 2 digits
Level 3: more detailed, 3 digits
Level 4: most detailed, 5 digits
Ethnicity codes: level 1 - code, ethnicity, priority
1: European (6)
2: Maori (1)
3: Pacific (2)
4: Asian (3)
5: Middle Eastern/Latin American/African - MELAA (4)
6: Other ethnicity (5)
9: Residual categories (9)
Ethnicity coding: minimum level recorded
Level 4
Numerator : denominator bias
A common error in health research where researchers need to adjust for the classification differences when 2 diff output methods are used
Numerator: prioritised output
Denominator: total response output
Ethnicity coding: repetitions in level 3, 2, 1
Don’t report repeated codes twice
Relative inequality and absolute inequality
Similar to RR and RD
Relative inequality: EGO/CGO
Absolute inequality: EGO - CGO
How to interpret relative inequality
e.g. relative inequality = 2
x are twice as likely to smoke as y
OR x are 2 times more likely to smoke as y
OR x are 100% more likely to smoke than y (RRI = (RR - 1) x 100%)
If result < 1, interpret it in %, e.g. relative inequality = 0.25
x are 75% less likely to to smoke than y (RRR = (1 - RR) x 100%)
How to interpret absolute inequality
e.g. absolute inequality = 10 per 100
There are 10 more smokers per 100 x than per 100 y
OR out of 100 x, there are 10 more smokers than out of 100 y
If result is negative, e.g. absolute inequality = -15 per 100
There are 15 fewer smokers per 100 x than per 100 y
OR out of 100 x, there are 15 fewer smokers than out of 100 y
