Physical activity opportunities in low socioeconomic status neighbourhoods

Exploring the association between low socioeconomic status and cardiovascular disease risk in healthy Greeks, in the years of financial crisis (2002-2012): The ATTICA study

BACKGROUND

Despite recent declines in mortality, cardiovascular disease (CVD) remains the leading cause of death in Europe today. Given the fact that many of the biological risk factors have already been identified, researchers still search for different modifiable factors that may influence CVD risk, among which SES gathers a great part of interest.

AIMS

To explore the effect of low socioeconomic status (SES) on a 10-year cardiovascular disease (CVD) incidence, in the years of financial crisis.

METHODS

This population-based study was carried out in the province of Attica, where Athens is a major metropolis. During 2001-2002, information from 1528 men (18-87years old) and 1514 women (18-89years old) was collected. Educational level and annual income were used to define their SES. After a 10-year of follow-up period (2002-2012), CVD incidence was recorded.

RESULTS

Low compared to high SES class, at the ages above 45years, was independently associated with increased 10-year CVD incidence [adjusted odds ratio and 95% confidence interval: 2.7 (1.5, 4.9)] but not among the younger participants. SES was also negatively associated with psychological components (all p-values<0.001), diabetes mellitus (p=0.002), obesity (p=0.087) and physical activity (p=0.056).

CONCLUSION

There is evidence for a consistent reverse relation between SES and the incidence of CVD and for higher CVD risk factors among less privileged individuals. The striking differences by SES underscore the critical need to improve screening, early detection, and treatment of CVD-related conditions for people of lower SES, emphasizing in the middle-aged groups.

Do Neighborhood Physical Activity Resources and Land Use Influence Physical Activity among African American Public Housing Residents?

Few studies have examined neighborhood influences on physical activity (PA) among low-income African Americans living in public housing. This study measured the associations of PA resources and land use with PA among 216 African Americans living in 12 low-income housing developments in Houston, Texas. Neighborhood measures included both detailed information from in-person audits and geographic information systems (GIS) data. Hierarchical linear regression models tested the associations of neighborhood PA resource availability and quality and land use density and diversity with individual-level, self-reported PA. Land use diversity was positively associated with walking among men after controlling for other neighborhood characteristics. Policies that promote land use diversity or improve the pedestrian environment in areas with diverse destinations may encourage PA among public housing residents.

Neighborhood sampling: how many streets must an auditor walk?

This study tested the representativeness of four street segment sampling protocols using the Pedestrian Environment Data Scan (PEDS) in eleven neighborhoods surrounding public housing developments in Houston, TX. The following four street segment sampling protocols were used (1) all segments, both residential and arterial, contained within the 400 meter radius buffer from the center point of the housing development (the core) were compared with all segments contained between the 400 meter radius buffer and the 800 meter radius buffer (the ring); all residential segments in the core were compared with (2) 75% (3) 50% and (4) 25% samples of randomly selected residential street segments in the core. Analyses were conducted on five key variables: sidewalk presence; ratings of attractiveness and safety for walking; connectivity; and number of traffic lanes. Some differences were found when comparing all street segments, both residential and arterial, in the core to the ring. Findings suggested that sampling 25% of residential street segments within the 400 m radius of a residence sufficiently represents the pedestrian built environment. Conclusions support more cost effective environmental data collection for physical activity research.