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A synthetic population of Sweden: datasets of agents, households, and activity-travel patterns.

ABSTRACT: A synthetic population is a simplified microscopic representation of an actual population. Statistically representative at the population level, it provides valuable inputs to simulation models (especially agent-based models) in research areas such as transportation, land use, economics, and epidemiology. This article describes the datasets from the Synthetic Sweden Mobility (SySMo) model using the state-of-art methodology, including machine learning (ML), iterative proportional fitting (IPF), and probabilistic sampling. The model provides a synthetic replica of over 10 million Swedish individuals (i.e., agents), their household characteristics, and activity-travel plans. This paper briefly explains the methodology for the three datasets: Person, Households, and Activity-travel patterns. Each agent contains socio-demographic attributes, such as age, gender, civil status, residential zone, personal income, car ownership, employment, etc. Each agent also has a household and corresponding attributes such as household size, number of children ≤ 6 years old, etc. These characteristics are the basis for the agents' daily activity-travel schedule, including type of activity, start-end time, duration, sequence, the location of each activity, and the travel mode between activities.

SUBMITTER: Tozluoglu C

PROVIDER: S-EPMC10205447 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature

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A synthetic population of Sweden: datasets of agents, households, and activity-travel patterns.

Tozluoğlu Çağlar Ç Dhamal Swapnil S Yeh Sonia S Sprei Frances F Liao Yuan Y Marathe Madhav M Barrett Christopher L CL Dubhashi Devdatt D

Data in brief 20230507

A synthetic population is a simplified microscopic representation of an actual population. Statistically representative at the population level, it provides valuable inputs to simulation models (especially agent-based models) in research areas such as transportation, land use, economics, and epidemiology. This article describes the datasets from the Synthetic Sweden Mobility (<i>SySMo</i>) model using the state-of-art methodology, including machine learning (ML), iterative proportional fitting ( ...[more]

PMID: 37228419

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Project description:BackgroundEnvironmental characteristics may be associated with patterns of physical activity in general or with particular types of physical activity such as active travel (walking or cycling for transport). However, most studies in this field have been conducted in North America and Australia, and hypotheses about putative correlates should be tested in a wider range of sociospatial contexts. We therefore examined the contribution of putative personal and environmental correlates of active travel and overall physical activity in deprived urban neighbourhoods in Glasgow, Scotland as part of the baseline for a longitudinal study of the effects of opening a new urban motorway (freeway).MethodsWe conducted a postal survey of a random sample of residents (n = 1322), collecting data on socioeconomic status, perceptions of the local environment, travel behaviour, physical activity and general health and wellbeing using a new 14-item neighbourhood rating scale, a travel diary, the short form of the International Physical Activity Questionnaire (IPAQ) and the SF-8. We analysed the correlates of active travel and overall physical activity using multivariate logistic regression, first building models using personal (individual and household) explanatory variables and then adding environmental variables.ResultsActive travel was associated with being younger, living in owner-occupied accommodation, not having to travel a long distance to work and not having access to a car, whereas overall physical activity was associated with living in social rented accommodation and not being overweight. After adjusting for personal characteristics, neither perceptions of the local environment nor the objective proximity of respondents' homes to motorway or major road infrastructure explained much of the variance in active travel or overall physical activity, although we did identify a significant positive association between active travel and perceived proximity to shops.ConclusionApart from access to local amenities, environmental characteristics may have limited influence on active travel in deprived urban populations characterised by a low level of car ownership, in which people may have less capacity for making discretionary travel choices than the populations studied in most published research on the environmental correlates of physical activity.

Project description:BackgroundPhysical activity occurs across various domains including leisure/recreation, for transportation, or for work or household reasons. Rural and urban active living environments are characterized by different opportunities for physical activity within each domain which may translate into different patterns of behavior. The aim of this study was to compare rural-urban differences in physical activity across different domains, and explore interactions between sociodemographic factors, physical activity domains, and rurality.MethodsWe used self-reported data collected across three physical activity domains (active transportation, recreation, occupational/household) and relevant sociodemographic variables from the Canadian Community Health Survey. Adjusting for sociodemographic factors, we did two separate cross-sectional analyses: 1) binary logistic regression to determine the odds of reporting any activity in each domain, and 2) ordinary least squares regression using the sub-samples reporting > 0 min per week of activity to compare how much activity was reported in each domain.ResultsOur final survey weighted sample of Canadian adults (mean age 47.4 years) was n = 25,669,018 (unweighted n = 47,266). Rural residents were less likely to report any active transportation (OR = 0.59, 95% CI [0.51, 0.67], p < .0001). For recreational physical activity, rural males had lower odds (OR = 0.75, 95% CI [0.67, 0.83], p < .0001) and rural females had higher odds (OR = 1.19, 95% CI [1.08, 1.30], p = .0002) of reporting any participation compared to urban residents. Rural males (OR = 1.90, 95% CI [1.74, 2.07], p < .0001) and females (OR = 1.33, 95% CI [1.21, 1.46], p < .0001) had higher odds of reporting any occupational or household physical activity.ConclusionsUrban residents tend to participate in more active transportation, while rural residents participate in more occupational or household physical activity. Location-based differences in physical activity are best understood by examining multiple domains and must include appropriate sociodemographic interactions, such as income and sex/gender.

Project description:BackgroundThe need to promote a healthy diet to curb the current obesity epidemic has today been recognized by most countries. A prerequisite for planning and evaluating interventions on dietary intake is the existence of valid information on long-term average dietary intake in a population. Few large, population-based studies of dietary intake have been carried out in Sweden. The largest to date is the Västerbotten Intervention Program (VIP), which was initiated in 1985, with data collection still ongoing. This paper reports on the first comprehensive analyses of the dietary data and presents dietary intake patterns among over 60,000 women and men in northern Sweden during 1992-2005.MethodsBetween 1992 and 2005, 71,367 inhabitants in Västerbotten county aged 30, 40, 50, and 60 years visited their local health care center as part of the VIP. Participants of VIP filled in an 84- or 64-item food frequency questionnaire (FFQ) and provided sociodemographic information. Complete and realistic information on consumption frequency was provided by 62,531 individuals. Food intake patterns were analyzed using K-means cluster analyses.ResultsThe mean daily energy intake was 6,83 (+/- 1,77) MJ among women and 8,71 (+/- 2,26) MJ among men. More than half of both women and men were classified as Low Energy Reporters (defined as individuals reporting a food intake level below the lower 95% confidence interval limit of the physical activity level). Larger variation in frequency of daily intake was seen among women than among men for most food groups. Among women, four dietary clusters were identified, labeled "Fruit and vegetables", "High fat", "Coffee and sandwich", and "Tea and ice cream". Among men, three dietary clusters were identified, labeled "Fruit and vegetables", "High fat", and "Tea, soda and cookies".ConclusionMore distinct food intake patterns were seen among women than men in this study in northern Sweden. Due to large proportions of Low Energy Reporters, our results on dietary intake may not be suitable for comparisons with recommended intake levels. However, the results on food intake patterns should still be valid and useful as a basis for targeting interventions to groups most in need.

Dataset Information

A synthetic population of Sweden: datasets of agents, households, and activity-travel patterns.

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A synthetic population of Sweden: datasets of agents, households, and activity-travel patterns.

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