Influence of households on drinking behaviour a multi level analysis
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Influence of Households on Drinking Behaviour: a Multi-level analysis. Roy Carr-Hill (and Nigel Rice) Centre for Health Economics University of York. Background. Long term heavy drinking associated with increased risk of wide range of conditions

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Influence of Households on Drinking Behaviour: a Multi-level analysis

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Influence of households on drinking behaviour a multi level analysis

Influence of Households on Drinking Behaviour: a Multi-level analysis

Roy Carr-Hill (and Nigel Rice)

Centre for Health Economics

University of York


Background

Background

  • Long term heavy drinking associated with increased risk of wide range of conditions

  • Drinking guidelines established to enable individuals to monitor alcohol consumption

  • Most research is on role of atomised (rational) consumer

  • Purpose of paper to explore influence of group, especially household, membership


Area or household effects

Area or Household Effects

  • Edwards et.al.(1994) social interaction theory

  • Four possible mechanisms:

  • Physical environment

  • Cultural milieu

  • Place deprivation

  • Selective mobility

  • Growing literature on importance of place, although often without sufficient controls

  • More fundamental groupings more likely


Data and methods

Data and methods

  • 1993 Health Survey for England 17,687 interviews aged 16+ living in 9,700 hhds

    SizeN hhds %

    13393 39

    2429949

    3 787 9

    4 218 2

    5+ 40(-)


Independent variables

Independent Variables

  • Personal: age, sex (NOT gender)

  • Social environment: persons in hhd, single or partnered, perceived social support

  • Health: perceived stress

  • Health related behaviour: physical activity

  • Education: formal qualifications

  • Socio-economic: car ownership, social class, economic activity, income support

  • Problem -other health variables - likely to be jointly determined with drinking


Dependent variable

Dependent Variable

  • N units of alcohol drunk in previous week

  • Empirical distributions highly skewed

  • Constant of unity added to all observations before taking natural logs

  • Other analysis (e.g. Sutton and Godfrey, 1995) relied on dummy variables to reflect other hhd members drinking

  • Assumed this is externality


Multi level framework

Multi-Level framework

  • Model area and household effects as random components

  • Allow for clustering (intra-class correlation) within both hhds and eventually areas

  • Three models specified

  • Basic model with age and sex

  • Individual model with individual variables

  • Full model with both hhd and indiv vars


Fixed effects

Fixed Effects

  • Males

  • Difference decreased with age

  • Single people consume more

  • Physically active consume more

  • Lack of social support had no effect

  • Economically inactive consume less but mitigated by hhd size and car ownership

  • Clear social class gradient

  • Those on income support consume less but effect disappear with hhd vars


Household characteristics and random level effects

Household characteristics and Random Level Effects

  • Household size important

  • Car ownership (reflecting permanent income)

  • Multiple car ownership

  • Most variance between individuals (56%) with 42% at hhd level and 2% area level

  • Once again geographical contextual vars are an academic hypothesis > a reality

  • With full model, proportions change to 55% individual, 39% hhds and 2% area


Conclusions i

Conclusions: I

  • Large proportion of unexplained variation in individual alcohol consumption can be attributed to household membership

  • Nearly as large as contribution of unexplained differences between indivs

  • Policies should address households as well as individuals and support analysis of impact of taxes on consumption levels


Conclusion ii

Conclusion: II

  • Intra-household effects are often important and can be addressed with many surveys

  • Especially important for attitudinal and behavioural variables

  • Place effects are often exaggerated


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