Dataset Information

How Does Walkability Change Behavior? A Comparison between Different Age Groups in the Netherlands.

ABSTRACT: Empirical research provides evidence that, in neighborhoods with higher walkability, individuals make more walking trips. However, it is not clear what the exact nature is of the relationships between neighborhood walkability and walking trips, since a higher walking frequency can be explained in different ways. This study examined whether the extra walking trips in better walkable neighborhoods are related primarily to trip generation, destination choice, or transport mode choice and whether this is the same for different age groups. A neighborhood fixed effects regression analysis was conducted in a first step to obtain a walkability measure for each neighborhood in the Netherlands including systematic as well as unobserved effects. Subsequently, the estimated fixed effects were used as walkability data for a path analysis based on a causal model to test the hypotheses stated. The results of the path analysis show direct relationships of neighborhood walkability with trip generation, destination choice, and transport mode choice, after controlling for the mutual relationships between the activity and trip variables. Comparing different age groups (i.e., children, adults, and elderly), the differences found mostly concerned the relationship between neighborhood walkability and trip generation. We concluded therefore that conditions for walkability are not the same for all age groups.

SUBMITTER: Liao B

PROVIDER: S-EPMC7013899 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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How Does Walkability Change Behavior? A Comparison between Different Age Groups in the Netherlands.

Liao Bojing B E W van den Berg Pauline P van Wesemael Pieter J V PJV A Arentze Theo T

International journal of environmental research and public health 20200115 2

Empirical research provides evidence that, in neighborhoods with higher walkability, individuals make more walking trips. However, it is not clear what the exact nature is of the relationships between neighborhood walkability and walking trips, since a higher walking frequency can be explained in different ways. This study examined whether the extra walking trips in better walkable neighborhoods are related primarily to trip generation, destination choice, or transport mode choice and whether th ...[more]

PMID: 31952143

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Project description:Aging is now the most profound risk factor for almost all non-communicable diseases. Studies have shown that probiotics play a specific role in fighting aging. We used metagenomic sequencing to study the changes in gut microbes in different age groups and found that aging had the most significant effect on subjects' gut microbe structure. Our study divided the subjects (n=614) into two groups by using 50 years as the age cut-off point for the grouping. Compared with the younger group, several species with altered abundance and specific functional pathways were found in the older group. At the species level, the abundance of Bacteroides fragilis, Bifidobacterium longum, Clostridium bolteae, Escherichia coli, Klebsiella pneumoniae, and Parabacteroides merdae were increased in older individuals. They were positively correlated to the pathways responsible for lipopolysaccharide (LPS) biosynthesis and the degradation of short-chain fatty acids (SCFAs). On the contrary, the levels of Barnesiella intestinihominis, Megamonas funiformis, and Subdoligranulum unclassified were decreased in the older group, which negatively correlated with the above pathways (p-value<0.05). Functional prediction revealed 92 metabolic pathways enriched in the older group significantly higher than those in the younger group (p-value<0.05), especially pathways related to LPS biosynthesis and the degradation of SCFAs. Additionally, we established a simple non-invasive model of aging, nine species (Bacteroides fragilis, Barnesiella intestinihominis, Bifidobacterium longum, Clostridium bolteae, Escherichia coli, Klebsiella pneumoniae, Megamonas funiformis, Parabacteroides merdae, and Subdoligranulum unclassified) were selected to construct the model. The area under the receiver operating curve (AUC) of the model implied that supplemented probiotics might influence aging. We discuss the features of the aging microbiota that make it more amenable to pre-and probiotic interventions. We speculate these metabolic pathways of gut microbiota can be associated with the immune status and inflammation of older adults. Health interventions that promote a diverse microbiome could influence the health of older adults.

Project description:BackgroundWalkability indices have been developed and linked to behavioural and health outcomes elsewhere in the world, but not comprehensively for Europe. We aimed to 1) develop a theory-based and evidence-informed Dutch walkability index, 2) examine its cross-sectional associations with total and purpose-specific walking behaviours of adults across socioeconomic (SES) and urbanisation strata, 3) explore which walkability components drive these associations.MethodsComponents of the index included: population density, retail and service density, land use mix, street connectivity, green space, sidewalk density and public transport density. Each of the seven components was calculated for three Euclidean buffers: 150 m, 500 m and 1000 m around every 6-digit postal code location and for every administrative neighbourhood in GIS. Componential z-scores were averaged, and final indices normalized between 0 and 100. Data on self-reported demographic characteristics and walking behaviours of 16,055 adult respondents (aged 18-65) were extracted from the Dutch National Travel Survey 2017. Using Tobit regression modelling adjusted for individual- and household-level confounders, we assessed the associations between walkability and minutes walking in total, for non-discretionary and discretionary purposes. By assessing the attenuation in associations between partial indices and walking outcomes, we identified which of the seven components drive these associations. We also tested for effect modification by urbanization degree, SES, age and sex.ResultsIn fully adjusted models, a 10% increase in walkability was associated with a maximum increase of 8.5 min of total walking per day (95%CI: 7.1-9.9). This association was consistent across buffer sizes and purposes of walking. Public transport density was driving the index's association with walking outcomes. Stratified results showed that associations with minutes of non-discretionary walking were stronger in rural compared to very urban areas, in neighbourhoods with low SES compared to high SES, and in middle-aged (36-49 years) compared to young (18-35 years old) and older adults (50-65 years old).ConclusionsThe walkability index was cross-sectionally associated with Dutch adult's walking behaviours, indicating its validity for further use in research.

Dataset Information

How Does Walkability Change Behavior? A Comparison between Different Age Groups in the Netherlands.

Publications

How Does Walkability Change Behavior? A Comparison between Different Age Groups in the Netherlands.

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