J M Noordzij1, M A Beenackers2, J Oude Groeniger2,3, E J Timmermans4,5, I Motoc4,5, M Huisman4,5, F J van Lenthe2,6. 1. Department of Public Health, Erasmus University Medical Center, P. O. Box 2040, 3000 CA, Rotterdam, Zuid-Holland, The Netherlands. j.m.noordzij@erasmusmc.nl. 2. Department of Public Health, Erasmus University Medical Center, P. O. Box 2040, 3000 CA, Rotterdam, Zuid-Holland, The Netherlands. 3. Department of Public Administration and Sociology, Erasmus University, Rotterdam, The Netherlands. 4. Department of Epidemiology and Data Science, Amsterdam Public Health Research Institute, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan, 1117, Amsterdam, The Netherlands. 5. Department of Sociology, Faculty of Social Sciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands. 6. Department of Human Geography and Spatial Planning, Utrecht University, Utrecht, The Netherlands.
Abstract
BACKGROUND: With urbanization and aging increasing in coming decades, societies face the challenge of keeping aging populations active. Land use mix (LUM) has been associated with cycling and walking, but whether changes in LUM relate to changes in cycling/walking is less known. OBJECTIVES: Our objective was to study the effect of LUM on cycling/walking in two Dutch aging cohorts using data with 10 years of follow-up. METHODS: Data from 1183 respondents from the Health and Living Conditions of the Population of Eindhoven and Surroundings (GLOBE) study and 918 respondents from the Longitudinal Aging Study Amsterdam (LASA) were linked to LUM in 1000-m sausage network buffers at three time-points. Cycling/walking outcomes were harmonized to include average minutes spent cycling/walking per week. Data was pooled and limited to respondents that did not relocate between follow-up waves. Associations between LUM and cycling/walking were estimated using a Random Effects Within-Between (REWB) model that allows for the estimation of both within and between effects. Sensitivity analyses were performed on smaller (500-m) and larger (1600-m) buffers. RESULTS: We found evidence of between-individual associations of LUM in 1000-m buffers and walking (β: 11.10, 95% CI: 0.08; 21.12), but no evidence of within-associations in 1000-m buffers. Sensitivity analyses using 500-m buffers showed similar between-associations, but negative within-associations (β: -35.67, 95% CI: - 68.85; - 2.49). We did not find evidence of between-individual associations of LUM in any buffer size and cycling, but did find evidence of negative within-associations between LUM in 1600-m buffers and cycling (β: -7.49, 95% CI: - 14.31; - 0.66). DISCUSSION: Our study found evidence of positive associations between LUM and average walking time, but also some evidence of negative associations between a change in LUM and cycling/walking. LUM appears to be related to cycling/walking, but the effect of changes in LUM on cycling/walking is unclear.
BACKGROUND: With urbanization and aging increasing in coming decades, societies face the challenge of keeping aging populations active. Land use mix (LUM) has been associated with cycling and walking, but whether changes in LUM relate to changes in cycling/walking is less known. OBJECTIVES: Our objective was to study the effect of LUM on cycling/walking in two Dutch aging cohorts using data with 10 years of follow-up. METHODS: Data from 1183 respondents from the Health and Living Conditions of the Population of Eindhoven and Surroundings (GLOBE) study and 918 respondents from the Longitudinal Aging Study Amsterdam (LASA) were linked to LUM in 1000-m sausage network buffers at three time-points. Cycling/walking outcomes were harmonized to include average minutes spent cycling/walking per week. Data was pooled and limited to respondents that did not relocate between follow-up waves. Associations between LUM and cycling/walking were estimated using a Random Effects Within-Between (REWB) model that allows for the estimation of both within and between effects. Sensitivity analyses were performed on smaller (500-m) and larger (1600-m) buffers. RESULTS: We found evidence of between-individual associations of LUM in 1000-m buffers and walking (β: 11.10, 95% CI: 0.08; 21.12), but no evidence of within-associations in 1000-m buffers. Sensitivity analyses using 500-m buffers showed similar between-associations, but negative within-associations (β: -35.67, 95% CI: - 68.85; - 2.49). We did not find evidence of between-individual associations of LUM in any buffer size and cycling, but did find evidence of negative within-associations between LUM in 1600-m buffers and cycling (β: -7.49, 95% CI: - 14.31; - 0.66). DISCUSSION: Our study found evidence of positive associations between LUM and average walking time, but also some evidence of negative associations between a change in LUM and cycling/walking. LUM appears to be related to cycling/walking, but the effect of changes in LUM on cycling/walking is unclear.
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