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Semelhante a Would addressing high-priority risk factors from the Global Burden of Disease (GBD) Study 2010 potentially reduce health inequalities?: A case study
Semelhante a Would addressing high-priority risk factors from the Global Burden of Disease (GBD) Study 2010 potentially reduce health inequalities?: A case study (20)
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Would addressing high-priority risk factors from the Global Burden of Disease (GBD) Study 2010 potentially reduce health inequalities?: A case study
1. 1
GHME Conference 2013
Would addressing high-priority risk
factors from the Global Burden of
Disease (GBD) Study 2010
potentially reduce health
inequalities?: A case study
Nick Wilson, Tony Blakely
University of Otago, Wellington, New Zealand
nick.wilson@otago.ac.nz
uow.otago.ac.nz/BODE3-info.html
2. Aim & Methods
Aim: To determine if addressing the top 10 risk factors
for a region in the GBD Study 2010 would help
reduce ethnic inequalities in health – using New
Zealand (NZ) as a case study.
Methods: Comparison with previous NZ work, literature
searches (RF distribution in NZ; availability of
preventive population-level interventions).
2
4. 4
Risk factor (as per GBD 2010 Study)
GBD 2010 –
Australasia
Region (Lim et
al 2012)
Previous (2004) risk
factor ranking for NZ
(Ministry of Health, 2004)
High body-mass index 1 6
Tobacco smoking, including SHS 2 2
High blood pressure 3 5
Alcohol use 4 13 (with other drugs)
Physical inactivity & low physical activity 5 7
High fasting plasma glucose 6 8 (pre-diabetes)
Diet low in fruits 7
10 (with low vegetable
intake)
Diet low in nuts and seeds 8 Not considered
High total cholesterol 9 4
Drug use 10 13 (with alcohol)
5. 5
Table 2: Evidence for unequal distribution of the top ten risk factors (Māori vs non-Māori)
Prioritized risk factor
[RF]
RF higher for
Māori vs non-
Māori? Evidence-base
High body-mass index + Many studies & national health surveys
Tobacco smoking,
including SHS
+ Many studies & national health surveys
(also for SHS exposure)
High blood pressure + Many studies & national nutrition surveys
Alcohol use + Many studies & national surveys
Physical inactivity & low
physical activity
+
(partial & women only)
Some studies – but inactivity only (no
differences by physical activity levels)
High fasting plasma
glucose
+ Many studies & national surveys
Diet low in fruits + Some studies & national surveys
Diet low in nuts and
seeds
+
(women only)
Just 1 national survey
High total cholesterol No Survey data
Drug use + Many studies & national surveys
6. 6
Figure 1: Rate ratios for selected risk factors for Māori men & women (relative to non-Māor)
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
Sedentary Cannabis in the
past year
High body-mass
(obese)
Hazardous
drinking of
alcohol
Tobacco smoking
(current)
Adjustedrateratios
Men Women
7. 7
Figure 2: Prevalence of hypertension and smoking for Māori vs non-Māori
0
5
10
15
20
25
30
35
40
45
50
Hypertension Tobacco smoking (current)
Prevalence(%)
Maori NZ European/Other
8. 8
Table 3: Extent of population-level preventive actions in NZ
Prioritized risk factor Level of response in NZ (prevention)
High body-mass index Minimal
Tobacco smoking, including
SHS
Relatively advanced internationally
(Smokefree 2025 goal, series of tax
increases, new marketing restrictions)
High blood pressure Minimal
Alcohol use Moderate (tax, laws)
Physical inactivity & low
physical activity
Minimal
High fasting plasma glucose Minimal
Diet low in fruits Minimal
Diet low in nuts and seeds Nil
High total cholesterol Minimal
Drug use Moderate (harm reduction, new law)
9. • Smokefree nation goal (<5% prevalence by 2025) –
strong Māori leadership.
• Ongoing annual tobacco tax increases (10%).
• Expanding outdoor smokefree areas – parks etc.
• Mass media campaigns; some Māori focus.
• Prohibited retail displays (in 2012)
• Plans for a plain packaging law.
• National quitline
9
Example: Tobacco control activities in NZ
Tariana Turia, Assoc Minister of
Health & Māori Party Leader
11. 11
Table 4: Examples of population-level preventive interventions reported as “cost-saving”
Prioritized RF Examples (refs in Wilson et al 2012 Bull WHO & available on request)
High body-mass index A 10% tax on unhealthy food; reduction of TV advertising (high fat/high sugar foods &
drinks); traffic light nutrition labeling.
Tobacco smoking,
including SHS
Tobacco taxation increases; “National Tobacco Campaign”.
High blood pressure Reduction of dietary salt; community heart health programs; use of a polypill.
Alcohol use Alcohol taxation increases, alcohol advertising restrictions, and restricting the number
of outlets.
Physical inactivity & low
physical activity
Mass media-based campaigns; community programs to encourage use of
pedometers
High fasting plasma
glucose
Nil identified (but some interventions still “cost-effective”).
Diet low in fruits Community-based fruit and vegetable promotion activities (1/24 interventions).
Diet low in nuts & seeds Nil identified.
High total cholesterol Community heart health programs; use of a polypill.
Drug use Supervised injection facility
12. 12
But limitations with the value of this evidence:
• Results of some health economic evaluations –
high uncertainty (eg, elasticities, attenuation
effects)
• While laws tend to impact on all ethnic groups –
less so for health promotion activities (unless: well
targeted, well-resourced communities)
• Only one NZ CEA within these 10 RF groups
(Quitline)
• Low political acceptability for some interventions in
NZ (eg, NZ economy dependent on fatty food
exports)
13. • GBD results for risk factors – good fit with
previous NZ work
• Most (9/10) RFs higher in Māori New
Zealanders (2 women only)
• NZ – fairly minimal response to preventing
these RFs (some exceptions, eg, smoking)
13
Conclusions (i)
14. For the 10 RFs:
• cost-effective population-level preventive
interventions available for 9/10
• cost-saving ones for 8/10
At least for NZ, acting on the GBD 2010 RF results
has good potential to:
• achieve health gain
• reduce health inequalities
• save health sector resources
14
Conclusions (ii)
What is our vision? Perhaps I can best convey this by some reflections of the last 6 or so year. First, in the previous work I have led we found – to my surprise – changing mortality and cancer inequalities over time. This led to a growing interest in cancer control. Second, I sat on the Cancer Control Council from 2005 to 2009 – this Council reports directly to the Minister to provide strategic advice on cancer control. Our task was to provide advice across the full range of cancer control, from prevention to palliation. During my time on the Council, I was struck by the near-complete absence of comparable information synthesis to assist prioritisation – despite both a burgeoning wealth of research information internationally, and what is actually very good quality data in New Zealand that was not being capitalised upon. This led to me talking to the Director General about undertaking a secondment in the Ministry of Health in 2009, with the express purposes of undertaking quantitative information synthesis and better harnessing the data we have. The DG confirmed my suspicions about the lack of comparative information synthesis for decision-making when he relayed to me the ‘100 manila folders’ approach to the annual planning process of the MoH. The ability to explicitly incorporate equity is also an imperative, and an academically challenging undertaking for academia. A strong focus on allowing an ability to compare from prevention to palliation, and strengthening collaborations with our Australian colleagues, also forms an underlying principle to BODE 3 . Finally, it is my view – and the view of my colleagues – that we are in desperate need for capacity building at the intersection of epidemiology and economic decision modelling in New Zealand. All this has lead to the development of BODE 3 – a research platform that we believe will offer the ability to undertake rapid assessments of cancer control and preventive interventions. It is firmly based on a range of rigorous methodological components, and unique and strong New Zealand data. But the totality of BODE 3 – to our knowledge – has not been undertaken elsewhere before. It is ambitious and innovative. It comes with risks, but it also comes with a huge potential to advance both academic rigour in these areas, and to inform and improve policy-making.