Neighbourhood Characteristics Predict Walking Among Dutch Elderly

Abstract

PURPOSE Many Dutch elderly (60%) do not meet health-enhancing physical activity recommendations. Among elderly walking is one of the most accessible and popular ways to be physically active. Neighbourhood characteristics of American cities are related to physical activity. The Netherlands has a different infrastructure. To guide efforts to promote walking in Dutch elderly, a study was performed to identify personal and environmental factors that are associated with walking in the neighbourhood. METHODS In three neighbourhoods of a Dutch city (Schiedam) a questionnaire and a walking diary were distributed among a stratified sample of independently living older adults (age 50–80 years). Neighbourhood characteristics were mapped by means of a checklist and analyzed with geographical information system (GIS) technology. Three models were developed with multivariate analyses; one model to explain walking duration (including personal, social, and perceived environmental factors), one model to explain walking frequency for four different motives: shopping, personal care, socializing, and pleasure (including personal factors, perceived and objective environmental factors, distance, and distribution of destinations), and one model to explain and predict the route elderly chose when walking. RESULTS On average the subjects (n=571, 68.1±6.9 yrs) walk 126±156 minutes per week in their neighbourhood. They cover about 800 m per walk. Shopping centres are found to be the most popular destination for walks. The walking duration in the neighbourhood is best predicted by age (rpartial=0.29), self-efficacy (rp=0.32), intention (rp=0.17), and frequency of walking outside the neighbourhood (rp=0.39) (explained variance: R2=0.35). The walking frequency is best predicted by age, gender, car use, destination, and the willingness to cover the distance to a certain destination. The chosen route can be predicted by the 'attractiveness' and the 'resistance' of streets. Examples of neighbourhood characteristics that contribute to the attractiveness of streets are the presence of parks, gardens, shops, pavement, and pedestrian crossings (R2=0.34). The presence of stairs, slopes, and fallow ground contribute to the resistance of streets (R2=0.08). CONCLUSIONS Characteristics of the physical environment account for a substantial variation in walking frequency and route choice of older people, but not in walking duration. The three models developed in this study should be cross-validated in other neighbourhoods and samples.