clustering of unhealthy behaviours over time: implications for policy and practice

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Clustering of unhealthy behaviours over time: implications for policy and practice David Buck and Francesca Frosini The King’s Fund

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David Buck introduces the findings of our new report which looks at how four key risky behaviours - smoking, excessive drinking, poor diet and lack of exercise - cluster in the English population and how that is changing over time.

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Page 1: Clustering of unhealthy behaviours over time: implications for policy and practice

Clustering of unhealthy behaviours over time: implications for policy and practice

David Buck and Francesca FrosiniThe King’s Fund

Page 2: Clustering of unhealthy behaviours over time: implications for policy and practice

The number of multiple lifestyles has increasing impact on health

...but more on mortality than reported quality of life.Source: EPIC-Norfolk cancer studies

Page 3: Clustering of unhealthy behaviours over time: implications for policy and practice

Research, policy and practice questions

What has been happening over time?– How has the distribution of multiple risk factors changed?– Have multiple risk factors been polarising between socio-economic groups?

What might this mean for policy?– Looking beyond single issue behaviour strategies– Design of incentives and guidance such as public health tariffs, Quality

Outcomes Framework, the Public Health Outcomes Framework and NICE public health guidance

What might this mean for practice?– Are we wasting resources and increasing resistance by hitting the same

people with separate interventions and messages?– Joint Strategic Needs Assessments, joint strategies, how to reap the health

premium cost-effectively, role of health and wellbeing board partners?

Page 4: Clustering of unhealthy behaviours over time: implications for policy and practice

What we did

Cross-sectional analysis of the Health Survey for England 2003 and 2008– Adult sample (>=16), 14,607 individuals in 2003 and 14,912 in 2008– Four key risk factors: smoking, alcohol consumption, fruit and

vegetable consumption and physical activity levels– Based on whether meeting government guidelines

Analysis of– Changes in prevalence over time– Whether changes in prevalence are related to socio-economic position,

education, gender or age

Page 5: Clustering of unhealthy behaviours over time: implications for policy and practice

We found real improvements over time

Consistent with movements ‘down ladder’– Shedding three and four risky behaviours, maintaining one and two– Overall about a 20% drop in three+ behaviours for men and women– But, 70% of the population still have at least two risky behaviours

Page 6: Clustering of unhealthy behaviours over time: implications for policy and practice

Within this there are 16 possible risk factor combinations

Note: S=Smoking; D=Drinking; F= Fruit & Vegetable; P=Physical activity; 0 = no risk factors

Combinations of risk factors in 2003, by gender

Page 7: Clustering of unhealthy behaviours over time: implications for policy and practice

We found significant changes over time in some of these combinations...

Change in prevalence of combinations of multiple lifestyle risk factors between 2003 and 2008 by gender

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Combinations of lifestyle risk factors

Men

Women

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Note: S=Smoking; D=Drinking; F= Fruit&Vegetable; P=Physical activity; Capital letters= presence of risk factor; * = significant change

Page 8: Clustering of unhealthy behaviours over time: implications for policy and practice

...but improvements come from some sectors of the population and not others

Change in prevalence of multiple lifestyle risk factors between 2003 and 2008 for men in professionals and unskilled manual households

0

10

20

30

40

50

60

70

80

90

100

110

2003 - All pop 2008 - All pop 2003 -Professionals

2008 -Professionals

2003-Unskilled

2008 Unskilled

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Page 9: Clustering of unhealthy behaviours over time: implications for policy and practice

A public health success story with a worrying twist

A real improvement in multiple health behaviours– In 2003, about one in three of us weren’t adhering to government

guidelines on three or four of the behaviours – this had dropped to about one in four of us by 2008

Most of the improvement came from higher socio-economic and educated groups– Poorer groups saw little improvement, widening relative inequalities, ie,

people with no qualifications were more than five times as likely as those with higher education to engage in all four unhealthy behaviours in 2008, compared to three times as likely in 2003

‘Improving the health of the poorest fastest’?– Putting this right will be required if one of the coalition’s own criteria for

the success of its reforms is to be met

Page 10: Clustering of unhealthy behaviours over time: implications for policy and practice

Implications for policy

Single behaviour approaches are necessary, but are they sufficient?– An approach based on people as well as ‘issues’– Case for more targeted public health policies– Little current integration between public health and inequalities policy

Public health and NHS reform– Multiple behaviours in the Public Health Outcomes Framework,

informing the health premium, Quality Outcomes Framework and design of behaviour tariffs?

– Research and guidance on multiple behaviour change from NIHR, PHE and NICE

Page 11: Clustering of unhealthy behaviours over time: implications for policy and practice

Implications for practice

Health and wellbeing boards– Most local areas undertake similar surveys, re-analysis on these lines

will tell them what:• they need to prioritise in their Joint Health and Wellbeing Strategy• local authorities should take into account in their new public health

role• the NHS should prioritise as it rolls out ‘Every Contact Counts’

Services– The development of wellness services– Role of health trainers and community health champions– Training for staff delivering interventions

Page 12: Clustering of unhealthy behaviours over time: implications for policy and practice

But, we need to know more

Pushing the analysis further– Correlation with other behaviours and mental health– Longitudinal analysis, to assess the impact of life events– Understanding role of social capital, norms and networks

In order to intervene successfully we need to know– If having multiple risks makes behaviour change easier or harder?– Is it more effective to tackle risks in sequence or in tandem?– From a population health perspective, should there be a focus on one

risk rather than another?– How cost effective are different approaches to multiple risk from a

commissioner’s perspective?