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BACKGROUND: Improving social circumstances (eg, an increase in income, finding a job or moving into a good neighbourhood) may reduce tobacco use, but robust evidence on the effects of such improvements is scarce. Accordingly we investigated the link between changing social circumstances and changing tobacco smoking using repeated measures data. METHODS: 15 000 adults with at least two observations over three waves (each 2 years apart) of a panel study had data on smoking status, family, labour force, income and deprivation (both neighbourhood and individual). Fixed effects regression modelling was used. FINDINGS: The odds of smoking increased 1.42-fold (95% CI 1.16 to 1.74) for a one log-unit increase in personal income among 15-24-year-olds, but there was no association of increased smoking with an increase in income among 25+ year olds. Moving out of a family nucleus, increasing neighbourhood deprivation (eg, 1.83-fold (95% CI 1.18 to 2.83) increased odds of smoking for moving from least to most deprived quintile of neighbourhoods), increasing personal deprivation and moving into employment were all associated with increased odds of smoking. The number of cigarettes smoked a day changed little with changing social circumstances. INTERPRETATION: Worsening social circumstances over the short run are generally associated with higher smoking risk. However, there were counter examples: for instance, decreasing personal income among young people was associated with decreased odds of smoking, a finding consistent with income elasticity of demand (the less one's income, the less one can consume). This paper suggests that improving social circumstances is not always pro-health over the short run; a more nuanced approach to the social determinants of health is required. [ABSTRACT FROM AUTHOR]

Objective To extend the limited international evidence on youth in-vehicle second-hand smoke (SHS) exposure by examining trends in New Zealand, a country with a national smoke-free goal and indoors smoke-free environment legislation. Methods We tracked exposure rates and explored the associations between in-vehicle SHS exposure and smoking behaviours. In-home exposure was also examined for comparative purposes. Data were collected in annual surveys of over 25 000 year 10 school students (14-15-year olds) for a 7-year period (2006-2012). Questions covered smoking behaviour, exposure to smoking and demographics. Results Youth SHS exposure rates in-vehicle and in-home trended down slightly over time (p<0.0001 for both) with 23% exposed in-vehicle in the previous week in 2012. However, marked inequalities in exposure between ethnic groups, and by school-based socioeconomic position, persisted. The strongest association with SHS exposure was parental smoking (eg, for both parents versus neither smoking in 2012: in-vehicle SHS exposure adjusted OR: 7.4; 95% CI: 6.5 to 8.4). After adjusting for seven other factors associated with initiation, logistic regression analyses revealed statistically significant associations of in-vehicle SHS exposure with susceptibility to initiation and smoking. Conclusions The slow decline in SHS exposure in vehicles and the lack of progress in reducing relative inequalities is problematic. To accelerate progress, the New Zealand Government could follow the example of other jurisdictions and prohibit smoking in cars carrying children. Other major policy interventions, beside enhanced smoke-free environments, will also likely be required if New Zealand is to achieve its 2025 smoke-free nation goal. [ABSTRACT FROM AUTHOR]

Background There is increased interest in the effectiveness and cobenefits of measures to promote walking and cycling, including health gains from increased physical activity and reductions in fossil fuel use and vehicle emissions. This paper analyses the changes in walking and cycling in two New Zealand cities that accompanied public investment in infrastructure married with programmes to encourage active travel. Method Using a quasi-experimental two-group pre-post study design, we estimated changes in travel behaviour from baseline in 2011 to mid-programme in 2012, and postprogramme in 2013. The intervention and control cities were matched in terms of sociodemographic variables and baseline levels of walking and cycling. A face-to-face survey obtained information on walking and cycling. We also drew from the New Zealand Travel Survey, a national ongoing survey of travel behaviour, which was conducted in the study areas. Estimates from the two surveys were combined using meta-analysis techniques. Results The trips and physical activity were evaluated. Relative to the control cities, the odds of trips being by active modes (walking or cycling) increased by 37% (95% CI 8% to 73%) in the intervention cities between baseline and postintervention. The net proportion of trips made by active modes increased by about 30%. In terms of physical activity levels, there was little evidence of an overall change. Discussion Comparing the intervention cities with the matched controls, we found substantial changes in walking and cycling, and conclude that the improvements in infrastructure and associated programmes appear to have successfully arrested the general decline in active mode use evident in recent years. [ABSTRACT FROM AUTHOR]