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Study Design
Environmental variability
The IPEN goal is to study people from a broad range of socioeconomic strata who live in communities with a broad range of land use patterns. It is essential to have wide variation in land use patterns believed to be related to walking and cycling for transportation (land use mix, residential density, street connectivity, sidewalks). It is desirable to have good variation in environmental variables that may be related to recreational physical activity, such as access to recreational facilities and aesthetic qualities. The sampling goal can be achieved in several ways, depending on circumstances in each country. Since the goal is to study associations, not to estimate prevalence rates, it is not necessary to have representative population samples. The sampling frame can be a metropolitan area, a region of a country, or a whole country.
A. The preferred study design is the one used by the US (NQLS) and Australian (PLACE) studies. Four cells are created by high/low walkability and high/low income or SES. This design allows an examination of the association of walkability and physical activity in different income groups. Where adequate GIS data are not available, high/low walkability neighborhoods can be selected based on input from local experts such as city planners, geographers, or public health officials.
B. Random sample of the population (most applicable when there is a good distribution of SES and land use patterns)
C. Combination of random sampling and oversampling of people who live in rare land use types
D. Other methods to achieve a wide range of SES and land use types. If specific neighborhoods are targeted, there must be a total of at least 8 neighborhoods in the study.
The Neighborhood Quality of Life Study (NQLS) is an observational epidemiologic study designed to allow comparisons between neighborhoods stratified based on their “walkability” characteristics and median household income from Geographic Information System (GIS) and Census data. The primary aim of NQLS was to evaluate the relationships between objectively-defined high-walkable (n=16) and low-walkable (n=16) neighborhoods in the Seattle and Baltimore regions and physical activity levels in 2400 randomly selected adults. King County within the Seattle Region and the Baltimore-Washington DC region were chosen based on (a) the sophistication (i.e., detailed land use assignments of each parcel) and completeness of existing land use GIS databases, (b) the consistency in land use data across the metropolitan area (i.e., across jurisdiction boundaries), and (c) ample variability in walkability across neighborhoods within the metropolitan area. Other designs were considered, such as random selection of neighborhoods. However, the stratified neighborhood comparison design that selects neighborhoods with the highest versus lowest walkability values was chosen because it creates the greatest range in the primary independent variables related to walkability.
Other Study Features
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