Residential relocation trajectories and neighborhood density, mixed land use and access networks as predictors of walking and bicycling in the Northern Finland Birth Cohort 1966

• Main Authors: Kärmeniemi, Mikko, Lankila, Tiina, Ikäheimo, Tiina, Puhakka, Soile, Niemelä, Maisa, Jämsä, Timo, Koivumaa-Honkanen, Heli, Korpelainen, Raija
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: figshare 2019
• Subjects: Biotechnology; 59999 Environmental Sciences not elsewhere classified; FOS Earth and related environmental sciences; Ecology; FOS Biological sciences; Sociology; FOS Sociology; 69999 Biological Sciences not elsewhere classified; Developmental Biology; Cancer; Science Policy; 111714 Mental Health; FOS Health sciences; Northern Finland
• Online Access: https://dx.doi.org/10.6084/m9.figshare.c.4708025.v1; https://springernature.figshare.com/collections/Residential_relocation_trajectories_and_neighborhood_density_mixed_land_use_and_access_networks_as_predictors_of_walking_and_bicycling_in_the_Northern_Finland_Birth_Cohort_1966/4708025/1

Abstract Background Given the high global prevalence of physical inactivity, there is a need to design cities that support active modes of transportation. High density diverse neighborhoods with good access networks have been associated with enhanced walking and cycling, but there is a lack of large-scale longitudinal studies utilizing a life course perspective to model residential relocation trajectories. The objectives of the present longitudinal study were to model and visualize residential relocation trajectories between 31 and 46 years of age based on neighborhood density, mixed land use and access networks (DMA), and to assess neighborhood DMA as a predictor of self-reported regular walking and cycling and objectively measured physical activity. Methods Based on data from the Northern Finland Birth Cohort 1966 (N = 5947), we used self-reported regular walking and cycling and objectively measured physical activity as outcome variables and objectively assessed neighborhood DMA as the main explanatory variable. We conducted sequence analysis to model residential relocation trajectories, and generalized linear mixed models and Fisher’s exact test were used to explore longitudinal associations between neighborhood DMA and physical activity. Results Over 80% of the participants lived in a neighborhood with the same level of neighborhood DMA during the follow-up. Relocation occurred more often from higher to lower DMA neighborhoods than reverse. Increased neighborhood DMA was associated with increased regular walking (OR 1.03; 95% CI: 1.00, 1.05; p = 0.023) and cycling (OR 1.17; 95% CI: 1.12, 1.23; p