Module 3 Flashcards
(85 cards)
1
Q
SEP definition
A
The social and economic factors that influence what positions individuals or groups hold within the structure of a society
2
Q
Determinants requirements
A
Must be objective, measurable, and meaningful
3
Q
Measures of SEP
A
– Used to quantify the level of inequality within/between societies
– Highlight changes to population structures over time/between Census periods/ generations
– Needed to help understand the relationship between health & other social variables (age, sex, ethnicity)
– Have been associated with health & life chances for as long as social groups have existed
4
Q
Measuring SEP for individuals
A
Education, Income, Occupation, Housing, Assets and wealth
5
Q
Measuring SEP for pop
A
Area measures: Deprivation, Access
Population measures: Income inequality, Literacy rates, Gross Domestic Product (GDP) per capita
6
Q
SEP
Individual lifestyle factors
A
- Education: higher education => pick up ideas/messages more easily
- Occupation: Status/social standing. Higher paid jobs => more power on social spectrum
- Income: Purchase material goods/services & health
7
Q
SEP
Social and Community influences
A
- Your PARENTS education, occupation, income
– Commonly used to measure SEP in studies of children and adolescents
– Some evidence that your parent’s SEP is associated with own SEP
8
Q
SEP
Living and working conditions
A
- Use area-based measures of SEP
- Most common in NZ is the NZ Index of Deprivation (NZDep)
- Index of Multiple Deprivation (IMD) allows you to drill down to explore the drivers of area deprivation
– Other measures include
Social fragmentation and
Accessibility indices
9
Q
Social fragmentation
A
How well a society combines
10
Q
Accessibility indices
A
Potential access to resources (not realized access)
11
Q
Deprivation definition
A
State of observable/demonstrable disadvantage relative to the local community/wider society/nation to which an individual/family/group belongs
- Another way of measuring people’s relative position in society, but reports this based on where they live, not who the people themselves
- Measures focus on material deprivation
- Deprivation should be applied to conditions and quality of life that are of a lower standard than is ordinary in a particular society
12
Q
What does living in poverty refer to?
A
A lack of income and resources to obtain the normative standard of living.
13
Q
What is material deprivation?
A
Refers to what residents living in particular areas “don’t have”
14
Q
Variables in NZDep2013
O CLIQuIEST
A
Communication Living space Income Income Qualification Employment Support Transport Own home
15
Q
NZDep2013
Communication
A
People aged <65 with no access to the internet at home
16
Q
NZDep2013
Living space
A
People living in equivalised households below a bedroom occupancy threshold
17
Q
NZDep2013
Income x2
A
People aged 18-64 receiving a means tested benefit
and
People living in equivalised households with income below an income threshold
18
Q
NZDep2013
Qualification
A
People aged 18-64 without any qualifications
19
Q
NZDep2013
Employment
A
People aged 18-64 unemployed
20
Q
NZDep2013
Support
A
People aged <65 living in a single parent family
21
Q
NZDep2013
Transport
A
People with no access to a car
22
Q
NZDep2013
Own home
A
People not living in own home
23
Q
Use of NZ Dep2013
A
Planning and resource allocation. Research. Advocacy
24
Q
Interpretation from NZDep2013
A
“People living in the most deprived neighbourhoods …”
Deciles are inverse scores to school deciles. 10 is worst. 1 is best.
25
General Socioeconomic, cultural and environmental conditions
- Group populations with similar SEP levels together
– Cross-sectional or longitudinal analyses
– The New Zealand Census Mortality Study
– Using the Integrated Data Infrastructure
26
Global determinants
– Income inequality
– National income • GDP
– Literacy Rates
– Free trade agreements
27
Preston curve
- Income & life expectancy not linear
| - Countries with low GDP have low life expectancy
28
Population data purpose
- measuring trends in Births,Mortality, Morbidity, Migration
- more applied work Unemployment/benefit claimants/pensions, Crime, Health service utilisation, Voter turnout, Education pathways
29
Data sources for epidemiology
The Census (main), Estimated Resident Populations (ERP), Vital events, Health service utilisation and outcomes (HSU), Nationally representative surveys, Ad hoc surveys, The Integrated Data Infrastructure (IDI)
30
The Census
- Traditionally, to operationalise census data collection
- Enumeration officers’ to contact individual households
- Country divided into small areas “Meshblocks” ~100 people
- In 2018, online
31
ERP
Estimated Resident Populations
– An estimate of all people who usually live in NZ at a given date
– Does not typically break down by ethnic group
32
Vital events
– Births, deaths and marriages (Department of Internal Affairs maintain, but Stats NZ prepares reports)
33
HSU
Health service utilisation and outcomes
– Ministry of Health record and report publicly funded health information e.g. hospitalisations, blood tests, pharmaceutical dispensing
34
Nationally representative surveys
– e.g. the NZ Health Survey(~15,000 people/annum)
- MoH manages survey with key topics and ‘spotlight’ less common issues
- Self-reported health and health behaviours
35
Ad hoc surveys
– Student satisfaction survey, market research companies, etc - May not always be generalizable to the wider pop
36
IDI
– Large data repository that links de-identified data about people that have used Government services
- Uses routinely collected info from government (& other agencies)
- All information is de-identified & strict rules are in place to preserve confidentiality
- Data from many sources can be linked to create a pop based
- To be ‘counted’: have had an interaction with >1 of these agencies – i.e. health, education, tax, police, social development, ACC
* A large research database containing microdata about people and households.
* De-identified data from a range of government agencies, Statistics NZ surveys (inclu 2013 Census), and non-government organisations.
* Holds over 166 billion facts, using 1.22 terabytes of space (continually growing).
* Researchers use the IDI to answer complex questions to improve outcomes for NZders
37
IDI Pros
- Deidentified
- Linkable, enabling wide insights
- Accessed in a data safe haven
- View longitudinal/life long information
- Identify risk/protective factors
- Predictive risk modelling
- Evaluate effectiveness of particular interventions
- Identify characteristics of groups with positive/negative outcomes
- Tailor interventions to people based on these characteristics.
38
IDI cons
- Definition of resident population varies
- IDI is only as good as the data in it
- Inherent selection biases from the choice of sources of data
- Can't perform case management
- Can't identify specific individuals at risk or for a specific intervention
- Can't identify specific individuals who are abusing systems and enforce law.
39
Data considerations
- Ethics & data privacy/confidentiality
- Purpose of data collection vs use in analysis
- Population vs population samples
- Are the participants representative of the NZ population?
- Objective vs subjective measures of health
40
Population structure
Age & sex: male / female (biological)
41
Population composition
Other attributes ethnicity, level of education
42
Pop pyramids
| X axis
male = left female = right
43
Pop pyramids
| Y axis
Age: young to old bottom to top
44
Pop pyramids
| Bars
count or % of people
45
Events determine pop structure
- Age-sex structure is a function of previous patterns/trends of fertility, migration & mortality events e.g. # of women aged 40-45 today determined by births 40-45 years ago (depleted by deaths ±migration)
- Vital events affect structure in different ways/extents
• Changes in fertility rates, can be dramatic but will have a time lag - Changes in infant mortality rates have similar effect
• Changes in adult mortality rates less dramatic & less variable over time - spread over wider age range
- Migration can have dramatic effect, especially if the trend is age & sex specific e.g. post Christchurch earthquakes
46
Pop structure affects events
- Fertility, mortality and migration are not evenly distributed across the population by age and sex
• Fertility: women only, concentrated in young adult ages
• Mortality: highest among the very young and the elderly
• Migration: varies with sex and stage in the life cycle
- Age-sex structure has a crucial influence on the rates at which these events occur in the pop
47
Dependency ratios
| Child
0-14 years /working age x 100
48
Dependency ratios
| Elderly
Elderly ≥65/working age x 100
49
Dependency ratios
| Total
(Youth +elderly)/working age x 100
50
What is the working age?
15-64 years
51
What does the denominator (population structure) influence?
Analysis
52
Ethnic composition of NZ depends on?
– Data sources for numerator and denominator: Census, HSU, IDI, National Health Survey
– Ethnicity coding protocol used: Total Response, Prioritised, Sole/Combination
53
Numerical ageing
Absolute increase in the # of elderly (-Reflects previous demographic patterns
– Improvements in life expectancy)
e.g. High fertility rates 60yrs ago = larger # of elderly today
54
Structural ageing
Increase in the proportion of the pop that is elderly
| – Driven by decreases in fertility rates – Began occurring in the 1800s
55
How does Numerical and structural aging occur?
independently but usually converge
56
Natural decline
When deaths > births (combo of absolute + structural ageing). More elderly = more deaths
57
Absolute decline
When there is insufficient migration to replace the decreased births and increased deaths - Not expected to happen in NZ for 70+ years – Happening in some European/Asian countries
58
Inequalities
Measurable differences/variations in health. Differences in health experience/outcomes between diff pop groups (social gradient)
59
Inequities
Those inequalities that are deemed to be unfair/unjust. Relations of equal and unequal power (political, social and economic, justice and injustice)
60
Health inequities:
Differences in the distribution of resources/services across pop which do not reflect health needs.
61
MoH equity
In NZ, ppl have differences in health that are avoidable, unfair/unjust. Equity: Diff people with diff levels of advantage require diff approaches/resources to get equitable health outcomes.
62
Te Tiriti o Waitangi
- Mana whenua
| - Mataawaka
63
PROGRESS
* Place of residence
* Race/ethnicity/culture/language
* Occupation
* Gender/sex
* Religion
* Education
* Socioeconomic status
* Social capital
64
RD
Rate Difference
| – absolute measure – EGO-CGO
65
RR
Rate Ratio
– relative measure
– EGO/CGO
66
Why health inequalities should be reduced
* The equitable thing to do - unfair
* Health inequalities are avoidable
* They affect everyone
* There are economic benefits associated - cost effective
67
Where do inequities in health outcomes result from?
Inequities in opportunities
68
Lorenz curve - Gini Coefficient
The ratio of the area between the line of perfect equality and the observed Lorenz curve to the area between the line of perfect equality and the line of perfect inequality
Gini = (A) / (A+B)
69
Lorenz curve - Gini Coefficient
| if Gini = 0?
A very equal society
70
Lorenz curve - Gini Coefficient
| if Gini = 1?
A very unequal society
71
The implications of (income) inequities
- An unequal society
- Less social cohesion
- Less trust between groups
- Increased stress
- Reduced economic productivity
- Poorer health outcomes
72
Transport choices
Cost, Travel time/ability to wake up in the morning, Car parking, Bus/Train timetabling, Distance, Walkability, Access to car/bicycle, Cycleways/Footpaths, Connectivity, Safety, Availability of showers at destination,Convenience, Children, Weather, Hills, Stuff to carry, Exercise, Time outdoors, Peers, Bike storage, Age, Fitness level, Mobility, Gender, Habits, Society/cultural expectations
73
Promoting Sustainable Modes of Commuting
Northern Busway, City Rail Link, T2/T3/Bus Lanes, Northwestern Motorway, Dedicated Lanes for Cyclists, Dedicated Cycleway/Footpath – Grafton Gully, Queen Street-Walkability, Walking School Buses (big scale)
74
Cycling
| Health benefits
Reduce stress, promote weight loss, builds stamina/muscle strength, increases cardiovascular fitness/longevity, boosts immune system, aids in heart disease prevention
75
Cycling
| Health risks
Air pollution exposure & accidents
76
Impact of noise barriers on air pollution conc. adjacent to motorways
- 30% reduction on average in ultrafine particle exposure with barrier
77
More people will cycle in neighbourhoods with:
- Low traffic volume with low vehicle speed on residential streets
- Separate cycleways on high-traffic roads
- Mixed land use (residences, commercial entities and civic facilities all co-located) so that destinations are walkable/bikeable from home
78
IMD variables
| CHAInwHEEl
Crime, Health, Access, Income, Housing, Education, Employment
79
IMD
| Crime
The Crime Domain measures the risk of personal and material victimization (mostly theft, burglaries and assaults): damage to person or property
80
IMD
| Health
Identifies areas with a high level of ill health (hospitalizations, cancer) or mortality
81
IMD
| Access
Measures the cost and inconvenience of travelling to access basic services. Supermarkets, GPs, service stations, ECE, primary and intermediate schools
82
IMD
| Income
Captures the extent of income deprivation in a data zone by measuring state funded financial assistance to those with insufficient income
83
IMD
| Housing
Proportion of people living in overcrowded housing and the proportion living in rented accommodation
84
IMD
| Education
Captures youth disengagement and the proportion of the working age population without a formal qualification
85
IMD
| Employment
Measure the degree to which working age people are excluded from employment
