Dataset Information

Individual Characteristics Associated with Active Travel in Low and High Income Groups in the UK.

ABSTRACT: Active travel (AT) has gained increasing attention as a way of addressing low levels of physical activity. However, little is known regarding the relationship between income and AT. The aim of this study was to investigate characteristics associated with undertaking AT in an adult population and by low- and high-income groups. Data collected from the Physical Activity and the Rejuvenation of Connswater (PARC) study in 2017 were used. Participants were categorised into socio-economic groups according to their weekly household income, and were categorised as participating in 'no' AT or 'some' AT and 'sufficient' AT. Multivariable logistic regression explored characteristics associated with AT in the full cohort, and the low- and high-income groups separately. Variables associated with AT in the low-income group were body mass index (BMI), physical activity self-efficacy, marital status, long term illness, difficulty walking and housing tenure. For the high-income group, BMI, marital status, housing tenure and education were associated with AT. For both income groups, there were consistent positive associations with the action/maintenance phase of the stage of change model across all AT categories. The findings suggest that population sub-groups may benefit from targeted initiatives to support engagement in AT and prevent further widening of inequalities.

SUBMITTER: Lawlor ER

PROVIDER: S-EPMC8508371 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Individual Characteristics Associated with Active Travel in Low and High Income Groups in the UK.

Lawlor Emma R ER Hunter Ruth F RF Adlakha Deepti D Kee Frank F Tully Mark A MA

International journal of environmental research and public health 20211001 19

Active travel (AT) has gained increasing attention as a way of addressing low levels of physical activity. However, little is known regarding the relationship between income and AT. The aim of this study was to investigate characteristics associated with undertaking AT in an adult population and by low- and high-income groups. Data collected from the Physical Activity and the Rejuvenation of Connswater (PARC) study in 2017 were used. Participants were categorised into socio-economic groups accor ...[more]

PMID: 34639660

Similar Datasets

Project description:Incidence of road traffic collisions (RTCs), types of users involved, and healthcare requirement afterwards are essential information for efficient policy making. We analysed individual-level data from nationally representative surveys conducted in low- or middle-income countries (LMICs) between 2008-2019. We describe the weighted incidence of non-fatal RTC in the past 12 months, type of road user involved, and incidence of traffic injuries requiring medical attention. Multivariable logistic regressions were done to evaluate associated sociodemographic and economic characteristics, and alcohol use. Data were included from 90,790 individuals from 15 countries or territories. The non-fatal RTC incidence in participants aged 24-65 years was 5.2% (95% CI: 4.6-5.9), with significant differences dependent on country income status. Drivers, passengers, pedestrians and cyclists composed 37.2%, 40.3%, 11.3% and 11.2% of RTCs, respectively. The distribution of road user type varied with country income status, with divers increasing and cyclists decreasing with increasing country income status. Type of road users involved in RTCs also varied by the age and sex of the person involved, with a greater proportion of males than females involved as drivers, and a reverse pattern for pedestrians. In multivariable analysis, RTC incidence was associated with younger age, male sex, being single, and having achieved higher levels of education; there was no association with alcohol use. In a sensitivity analysis including respondents aged 18-64 years, results were similar, however, there was an association of RTC incidence with alcohol use. The incidence of injuries requiring medical attention was 1.8% (1.6-2.1). In multivariable analyses, requiring medical attention was associated with younger age, male sex, and higher wealth quintile. We found remarkable heterogeneity in RTC incidence, the type of road users involved, and the requirement for medical attention after injuries depending on country income status and socio-demographic characteristics. Targeted data-informed approaches are needed to prevent and manage RTCs.

Project description:ObjectivesTo examine whether there are associations between active travel and markers of a healthy, low-carbon (HLC) diet (increased consumption of fruit and vegetables (FV), reduced consumption of red and processed meat (RPM)).DesignCross-sectional analysis of a cohort study.SettingsPopulation cohort of over 500 000 people recruited from 22 centres across the UK. Participants aged between 40 and 69 years were recruited between 2006 and 2010.Participants412 299 adults with complete data on travel mode use, consumption of FV and RPM, and sociodemographic covariates were included in the analysis.Exposure measuresMutually exclusive mode or mode combinations of travel (car, public transport, walking, cycling) for non-work and commuting journeys.Outcome measuresConsumption of FV measured as portions per day and RPM measured as frequency per week.ResultsEngaging in all types of active travel was positively associated with higher FV consumption and negatively associated with more frequent RPM consumption. Cycling exclusively or in combination with walking was most strongly associated with increased dietary consumption of FV and reduced consumption of RPM for both non-work and commuting journeys. Overall, the strongest associations were between non-work cycling and FV consumption (males: adjusted OR=2.18, 95% CI 2.06 to 2.30; females: adjusted OR=2.50, 95% CI 2.31 to 2.71) and non-work cycling and RPM consumption (males: adjusted OR=0.57, 95% CI 0.54 to 0.60; females: adjusted OR=0.54, 95% CI 0.50 to 0.59). Associations were generally similar for both commuting and non-work travel, and were robust to adjustment with sociodemographic and behavioural factors.ConclusionsThere are strong associations between engaging in active travel, particularly cycling, and HLC dietary consumption, suggesting that these HLC behaviours are related. Further research is needed to better understand the drivers and dynamics between these behaviours within individuals, and whether they share common underlying causes.

Project description:BackgroundEnvironmental characteristics may be associated with patterns of physical activity. However, the development of instruments to measure perceived characteristics of the local environment is still at a comparatively early stage, and published instruments are not necessarily suitable for application in all settings. We therefore developed and established the test-retest reliability of a new scale for use in a study of the correlates of active travel and overall physical activity in deprived urban neighbourhoods in Glasgow, Scotland.MethodsWe developed and piloted a 14-item scale based on seven constructs identified from the literature (aesthetics, green space, access to amenities, convenience of routes, traffic, road safety and personal safety). We administered the scale to all participants in a random postal survey (n = 1322) and readministered the scale to a subset of original respondents (n = 125) six months later. We used principal components analysis and Varimax rotation to identify three principal components (factors) and derived summary scores for subscales based on these factors. We examined the internal consistency of these subscales using Cronbach's alpha and examined the test-retest reliability of the individual items, the subscale summary scores and an overall summary neighbourhood score using a combination of correlation coefficients and Cohen's kappa with and without weighting.ResultsPublic transport and proximity to shops were the items most likely to be rated positively, whereas traffic volume, traffic noise and road safety for cyclists were most likely to be rated negatively. Three principal components - 'safe and pleasant surroundings', 'low traffic' and 'convenience for walking' - together explained 45% of the total variance. The test-retest reliability of individual items was comparable with that of items in other published scales (intraclass correlation coefficients (ICCs) 0.34-0.70; weighted Cohen's kappa 0.24-0.59). The overall summary neighbourhood score had acceptable internal consistency (Cronbach's alpha 0.72) and test-retest reliability (ICC 0.73).ConclusionThis new scale contributes to the development of a growing set of tools for investigating the role of perceived environmental characteristics in explaining or mediating patterns of active travel and physical activity.

Project description:BackgroundThere is little evidence on the potential health benefits of active travel in low- and middle-income countries (LMICs). The aim of this study was to assess the association between levels of active travel and physical multi-morbidity (i.e., two or more chronic physical conditions) and individual physical conditions among community-dwelling adults aged 65 or older in six LMICs.MethodsData were analyzed from the World Health Organization's Study on Global Ageing and Adult Health (China, Ghana, India, Mexico, Russia, South Africa). Active travel (minutes / week) was assessed with questions of the Global Physical Activity Questionnaire (GPAQ) and presented in tertiles. Eleven chronic conditions (angina, arthritis, asthma, chronic back pain, chronic lung disease, diabetes, edentulism, hearing problems, hypertension, stroke, visual impairment) were assessed by self-report of diagnosis, symptoms, or blood pressure measurement. Multivariable logistic regression analysis was conducted to assess the association between levels of active travel, physical conditions and physical multi-morbidity.ResultsThe final sample consisted of 14,585 individuals aged ≥65 years (mean age = 72.6±0.1 years; 54.9% female). In the fully adjusted model, compared to the highest tertile, those in the lowest tertile of active travel had a 1.28 (95%CI = 1.06-1.54) times higher odds for physical multi-morbidity. The association between active travel and physical multi-morbidity was significantly mediated by affect (14.4%) and cognition (9.7%). With regard to individual conditions, hearing problems, hypertension, stroke, and visual impairment were particularly strongly associated with less active travel.ConclusionThe current data suggest that lower levels of active travel are associated with the presence of physical health conditions and physical multi-morbidity. This multi-national study offers potentially valuable insight for a number of hypotheses which may influence this relationship, although testing with longitudinal studies is needed.

Project description:IntroductionAdverse perinatal outcomes (APO) pose a significant global challenge, particularly in low- and middle-income countries (LMICs). This study aims to analyse two cohorts of high-risk pregnant women for APO to comprehend risk factors and improve prediction accuracy.MethodsWe considered an LMIC and a high-income country (HIC) population to derive XGBoost classifiers to predict low birth weight (LBW) from a comprehensive set of maternal and fetal characteristics including socio-demographic, past and current pregnancy information, fetal biometry and fetoplacental Doppler measurements. Data were sourced from the FeDoC (Fetal Doppler Collaborative) study (Pakistan, LMIC) and theIMPACT (Improving Mothers for a Better PrenAtal Care Trial) study (Spain, HIC), and included 520 and 746 pregnancies assessed from 28 weeks gestation, respectively. The models were trained on varying subsets of the mentioned characteristics to evaluate their contribution in predicting LBW cases. For external validation, and to highlight potential differential risk factors for LBW, we investigated the generalisation of these models across cohorts. Models' performance was evaluated through the area under the curve (AUC), and their interpretability was assessed using SHapley Additive exPlanations.ResultsIn FeDoC, Doppler variables demonstrated the highest value at predicting LBW compared with biometry and maternal clinical data (AUCDoppler, 0.67; AUCClinical, 0.65; AUCBiometry, 0.63), and its combination with maternal clinical data yielded the best prediction (AUCClinical+Doppler, 0.71). In IMPACT, fetal biometry emerged as the most predictive set (AUCBiometry, 0.75; AUCDoppler, 0.70; AUCClinical, 0.69) and its combination with Doppler and maternal clinical data achieved the highest accuracy (AUCClinical+Biometry+Doppler, 0.81). External validation consistently indicated that biometry combined with Doppler data yielded the best prediction.ConclusionsOur findings provide new insights into the predictive role of different clinical and ultrasound descriptors in two populations at high risk for APO, highlighting that different approaches are required for different populations. However, Doppler data improves prediction capabilities in both settings, underscoring the value of standardising ultrasound data acquisition, as practiced in HIC, to enhance LBW prediction in LMIC. This alignment contributes to bridging the health equity gap.

Dataset Information

Individual Characteristics Associated with Active Travel in Low and High Income Groups in the UK.

Publications

Individual Characteristics Associated with Active Travel in Low and High Income Groups in the UK.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets