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Journal of Preventive Medicine and Public Health ; : 227-233, 2018.
Article in English | WPRIM | ID: wpr-717257

ABSTRACT

OBJECTIVES: Chronic diseases, including back pain, result in significant patient morbidity and societal burden. Overall improvement in physical fitness is recommended for prevention and treatment. Walking is a convenient modality for achieving initial gains. Our objective was to determine whether neighbourhood walkability, acting as a surrogate measure of physical fitness, was associated with the presence of chronic disease. METHODS: We conducted a cross-sectional study of prospectively collected data from a prior randomized cohort study of 227 patients referred for tertiary assessment of chronic back pain in Ottawa, ON, Canada. The Charlson Comorbidity Index (CCI) was calculated from patient-completed questionnaires and medical record review. Using patients’ postal codes, neighbourhood walkability was determined using the Walk Score, which awards points based on the distance to the closest amenities, yielding a score from 0 to 100 (0-50: car-dependent; 50-100: walkable). RESULTS: Based on the Walk Score, 134 patients lived in car-dependent neighborhoods and 93 lived in walkable neighborhoods. A multivariate logistic regression model, adjusted for age, gender, rural postal code, body mass index, smoking, median household income, percent employment, pain, and disability, demonstrated an adjusted odds ratio of 2.75 (95% confidence interval, 1.16 to 6.53) times higher prevalence for having a chronic disease for patients living in a car-dependent neighborhood. There was also a significant dose-related association (p=0.01; Mantel-Haenszel chi-square=6.4) between living in car-dependent neighbourhoods and more severe CCI scores. CONCLUSIONS: Our findings suggest that advocating for improved neighbourhood planning to permit greater walkability may help offset the burden of chronic disease.


Subject(s)
Humans , Awards and Prizes , Back Pain , Body Mass Index , Canada , Chronic Disease , Cohort Studies , Comorbidity , Cross-Sectional Studies , Employment , Family Characteristics , Logistic Models , Medical Records , Odds Ratio , Physical Fitness , Prevalence , Prospective Studies , Residence Characteristics , Smoke , Smoking , Walking
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