Do ‘environmental bads’ such as alcohol, fast food, tobacco, and gambling outlets cluster and co-locate in more deprived areas in Glasgow City, Scotland?

There is growing concern with the increasing prevalence of obesity in industrialised countries, a trend that is more apparent in the poor than in the rich. In an ecological study, the relationship between an area measure of socioeconomic status (SES) and the density of fast-food outlets was examined as one possible explanation for the phenomenon. It was found that there was a dose-response between SES and the density of fast-food outlets, with people living in areas from the poorest SES category having 2.5 times the exposure to outlets than people in the wealthiest category. The findings are discussed.

To better understand pathological gambling, potential risk factors were assessed within three domains--gambling behaviors, substance abuse and other problem behaviors, and sociodemographic factors. A random-digit-dial telephone survey was conducted in 1999-2000 with a representative sample of the U.S. population aged 18 or older. The current analyses uses data from the 2168 respondents who gambled in the year before the interview. Gambling measures included the Diagnostic Interview Schedule (DIS)-IV for pathological gambling, frequency of 15 types of gambling, and size of win or loss on the last occasion. Other measures included the quantity and frequency of alcohol consumption, frequency of illicit drug use and criminal offending, and the DIS-IV for alcohol and drug abuse and dependence. Results showed that casino gambling is associated with a high risk of gambling pathology. Lottery, cards, and bingo are associated with a moderately high risk of gambling pathology. Participation in a greater number of types of gambling is strongly predictive of gambling pathology, even after frequency of gambling and size of win or loss are taken into account. Alcohol abuse is strongly predictive of gambling pathology, even with gambling behaviors held constant. Minority and low socioeconomic status (SES) group members have higher levels of gambling pathology than other groups after all other factors are considered.

It has commonly been suggested that in modern cities individual or household deprivation (for example, low income or education) is amplified by area level deprivation (for example, lack of jobs or good schools), in ways which damage the health of the poorest and increase health inequalities. The aim of this study was to determine the location of a range of resources and exposures by deprivation in a UK city. We examined the location of 42 resources in Glasgow City, Scotland, in 2005–2006, by quintile of small area deprivation. Measures included number per 1000 population, network distance to nearest resource, and percentage of data zones containing at least one of each type of resource. Twelve resources had higher density in, and/or were closer to or more common in, more deprived neighbourhoods: public nurseries, public primary schools, police stations, pharmacies, credit unions, post offices, bus stops, bingo halls, public swimming pools, public sports centres, outdoor play areas, and vacant and derelict land/buildings. Sixteen had higher density in, and/or were closer to, or more common in, more affluent neighbourhoods: public secondary schools, private schools, banks, building societies, museums/art galleries, railway stations, subway stations, tennis courts, bowling greens, private health clubs, private swimming pools, colleges, A & E hospitals, parks, waste disposal sites, and tourist attractions. Private nurseries, Universities, fire stations, general, dental and ophthalmic practices, pawn brokers, ATMs, supermarkets, fast food chains, cafes, public libraries, golf courses, and cinemas showed no clear pattern by deprivation. Thus it appears that in the early 21st century access to resources does not always disadvantage poorer neighbourhoods in the UK. We conclude that we need to ensure that theories and policies are based on up-to-date and context-specific empirical evidence on the distribution of neighbourhood resources, and to engage in further research on interactions between individual and environmental factors in shaping health and health inequalities.