| Literature DB >> 21477347 |
Geoff Wong1, Ray Pawson, Lesley Owen.
Abstract
BACKGROUND: Legislation is one of the most powerful weapons for improving population health and is often used by policy and decision makers. Little research exists to guide them as to whether legislation is feasible and/or will succeed. We aimed to produce a coherent and transferable evidence based framework of threats to legislative interventions to assist the decision making process and to test this through the 'case study' of legislation to ban smoking in cars carrying children.Entities:
Mesh:
Year: 2011 PMID: 21477347 PMCID: PMC3079647 DOI: 10.1186/1471-2458-11-222
Source DB: PubMed Journal: BMC Public Health ISSN: 1471-2458 Impact factor: 3.295
Figure 1Simplified diagrammatic representation of potential threats to legislation (our initial framework). Threats in bold font are the ones which were most prominent and relevant in our test case study of legislation banning smoking in vehicles carrying children.
This figure has been highly simplified and for illustrative purposes has displayed the potential threats in a linear sequence.
The key questions that need to be addressed in the identified threats to legislation banning smoking in vehicles carrying children
| 1. PROBLEM MISIDENTIFICATION |
|---|
| Is the severity of the problem sufficient to justify a law? |
| a. Is it possible to show that exposure to second-hand smoke in cars leads to ill-health? |
| b. What toxicity levels are encountered in a car when cigarettes are smoked? |
| c. Does ventilation make a difference? |
| d. Are the toxicity levels comparable to other risky environments in which smoking bans already operate? |
| e. How does the potential harm compare to formally approved air quality standards? |
| 2. LACK OF PUBLIC SUPPORT |
| |
| a. What is the overall magnitude of support for such a law? |
| b. What are the levels of support amongst smokers? |
| c. What is the motivation behind public support? |
| d. Does endorsement depend on the extent and success of previous smoking bans in work and public places? |
| 3. LOBBY GROUP OPPOSITION |
| |
| a. Has the Tobacco lobby opposed this particular ban? |
| b. Are they likely to do so in future? |
| 4. ENFORCEMENT |
| |
| a. Given that the potential infraction is fleeting and localised will smokers fail to comply assuming there is little risk of being caught? |
| b. Given limited resources, the difficulties of detection and the fact that the law addresses a public health issue will the police act significantly on enforcement? |
| c. What other measure need to be incorporated to encourage compliance and enhance enforcement? |
Figure 2Flow diagram illustrating search process and article disposition.
Levels of self declared support for and/or practice of smoking bans in vehicles carrying children reported in included studies by smoking status (in date order)
| Study | Year of survey data collection | Type of data reported (support and/or practice of ban) | Country | Cars | ||
|---|---|---|---|---|---|---|
| Non-smokers and smokers support/practice % | Non-smokers support/practice % | Smokers support/practice % | ||||
| Bauman et al[ | 1994 | Support | Australia, NSW | 72 | 63 | |
| Norman et al[ | 1996/7 | Practice | USA, California | 66.0 (16.0 *) | ||
| Walsh et al[ | 2000 | Support and practice [in brackets] | Australia, NSW | 58.8 [86.7] | 44.7 [39.8] | |
| Kegler et al[ | 2000 | Practice | USA, Oklahoma State (North East) | 67.4 | 12.8 | |
| Binns et al[ | 2001 | Practice | USA, Chicago | 83.0 | 58.0 | |
| King et al[ | 2001 | Practice | USA, nationwide (African Americans only) | 84.1 | 21.4 | |
| McMillen et al[ | 2002 | Practice | USA, nationwide | 83.2 (urban) 68.7 (rural) ** | ||
| Gonzales et al[ | 2003/4 | Practice | USA, Albuquerque (Hispanics only) | 81.0 | ||
| Walsh et al[ | 2004 | Support | Australia, NSW | 55.6 | 50.5 | |
| Leatherdale et al[ | 2004 | Support | Canada, nationwide | 91.8 | 72.9 | |
| Kegler et al[ | 2004/5 | Practice | USA, Georgia (South West) | 36.8 (40.4 *) | ||
| Leatherdale et al[ | 2006 | Support | Canada, nationwide | 90.3 | 79.2 | |
| Jalleh et al[ | 2006# | Support | Australia, Western Australia | 87 | 80 | |
| Thomson et al[ | 2007/8 | Support | New Zealand, nationwide | 95.9 | ||
| Dunn et al[ | 2008 | Support | Australia, Queensland | 82.9*** | 76.9*** | |
Key: * % support if ban was only partial
** % support differentiated by rural and urban responders
# year of publication
*** % support refers only to children aged 12 or under present in the car
Impact of legislation on non-compliance reported by included studies on mobile phone usage in vehicles
| Data for non-compliance | |||||
|---|---|---|---|---|---|
| Study | Location | Pre legislation % (sampling interval before legislation) | Post legislation % - Time 1 (sampling interval after legislation) | Post legislation % - Time 2 (sampling interval after legislation) | Method used to obtain data |
| Johal et al[ | UK, Birmingham | 1.85 (10 weeks) | 0.97 (10 weeks) | 1.63 (24 months) | Direct observation of usage |
| Walker et al[ | UK, London | 2.3 (4 weeks) | 2.6 (4 weeks) | - | Direct observation of usage |
| Broughton[ | UK, London | - | - | 2.6 (36 months) | Direct observation of usage |
| Constant et al[ | France, nationwide | 4.2 (24 months) | 2.2 (24 months) | - | Self report of usage |
| Foss et al[ | US, North Carolina | 11.0 (4 to 8 weeks) | 11.8 (20 weeks) | - | Direct observation of usage |
| Mccartt et al. [ | US, New York City | 2.3 (24 weeks) | 1.1 (16 weeks) | 2.1 (12 months) | Direct observation of usage |
| Mccartt et al[ | US, Washington DC | 6.1 (12 weeks) | 3.5 (12 weeks) | 4.0 (12 months) | Direct observation of usage |
| Rajalin et al[ | Finland, nationwide | 55.8 (no data) | 15.2 (no data) | 20.0 (no data) | Self report of usage |
Key: * data on under 18 year olds only
Impact of legislation on compliance or injuries/fatalities reported by included studies on child restraints usage in vehicles
| Data for compliance | ||||
|---|---|---|---|---|
| Study | Location | Pre legislation % (sampling interval before legislation) | Post legislation % (sampling interval after legislation) | Method used to obtain data |
| Collarile et al[ | Italy, North East | 74.7 (12 months) | 92.5 (12 months) | Self report of usage |
| Murrin et al[ | USA, California | 5.6 (no data) | 11 (no data) | Direct inspection of usage |
| Rock et al[ | USA, Illinois | 301 (48 months) | 293 (48 months) | Database (Illinois Department of Transportation) |
| Margolis et al[ | USA, North Carolina | 2.19% (66 months) | 1.82% (104 months) | Database (North Carolina Collision Reports) |
| Desapriya et al[ | Japan, nationwide | No change reported (24 months) | No change reported (24 months) | Database (Traffic Bureau of National Police Agency and Institute for Traffic Accident Research and Data Analysis) |