Background: The Ultra-Low Emission Zone (ULEZ), introduced in Central London in April 2019, aims to enhance air quality and improve public health. The Children's Health in London and Luton (CHILL) study evaluates the impact of the ULEZ on children's health. This analysis focuses on the one-year impacts on the shift towards active travel to school.
Methods: CHILL is a prospective parallel cohort study of ethnically diverse children, aged 6-9 years attending 84 primary schools within or with catchment areas encompassing London's ULEZ (intervention) and Luton (non-intervention area). Baseline (2018/19) and one-year follow-up (2019/20) data were collected at school visits from 1992 (58%) children who reported their mode of travel to school 'today' (day of assessment). Multilevel logistic regressions were performed to analyse associations between the introduction of the ULEZ and the likelihood of switching from inactive to active travel modes, and vice-versa. Interactions between intervention group status and pre-specified effect modifiers were also explored.
Results: Among children who took inactive modes at baseline, 42% of children in London and 20% of children in Luton switched to active modes. For children taking active modes at baseline, 5% of children in London and 21% of children in Luton switched to inactive modes. Relative to the children in Luton, children in London were more likely to have switched from inactive to active modes (OR 3.64, 95% CI 1.21-10.92). Children in the intervention group were also less likely to switch from active to inactive modes (OR 0.11, 0.05-0.24). Moderator analyses showed that children living further from school were more likely to switch from inactive to active modes (OR 6.06,1.87-19.68) compared to those living closer (OR 1.43, 0.27-7.54).
Conclusions: Implementation of clean air zones can increase uptake of active travel to school and was particularly associated with more sustainable and active travel in children living further from school.
Background: Encouraging alternatives to the car such as walking, cycling or public transport is a key cross-sector policy priority to promote population and planetary health. Individual travel choices are shaped by individual and environmental contexts, and changes in these contexts - triggered by key events - can translate to changes in travel mode. Understanding how and why these changes happen can help uncover more generalisable findings to inform future intervention research. This study aimed to identify the mechanisms and contexts facilitating changes in travel mode.
Methods: Prospective longitudinal qualitative cohort study utilising semi-structured interviews at baseline (in 2021), three- and six-month follow up. Participants were residents in a new town in Cambridgeshire, UK, where design principles to promote walking, cycling and public transport were used at the planning stage. At each interview, we followed a topic guide asking participants about previous and current travel patterns and future intentions. All interviews were audio recorded and transcribed. Data analysis used the framework approach based on realist evaluation principles identifying the context and mechanisms described by participants as leading to travel behaviour change.
Results: We conducted 42 interviews with 16 participants and identified six mechanisms for changes in travel mode. These entailed increasing or reducing access, reliability and financial cost, improving convenience, increasing confidence and raising awareness. Participants described that these led to changes in travel mode in contexts where their existing travel mode had been disrupted, particularly in terms of reducing access or reliability or increasing cost, and where there were suitable alternative travel modes for their journey. Experiences of the new travel mode played a role in future travel intentions.
Implications: Applying realist evaluation principles to identify common mechanisms for changes in travel mode has the potential to inform future intervention strategies. Future interventions using mechanisms that reduce access to, reduce reliability of, or increase the financial cost of car use may facilitate modal shift to walking, cycling and public transport when implemented in contexts where alternative travel modes are available and acceptable.
Background: Knowledge of developmental trends in meeting age-specific 24-hour movement behaviour guidelines is lacking. This study describes developmental trends in device-measured physical activity and sedentary time over a three-year period among Western Australian children aged two to seven years, including differences between boys and girls. The proportion of children meeting age-specific physical activity guidelines before and after they transition to full-time school was also examined.
Methods: Data from waves 1 and 2 of the Play Spaces and Environments for Children's Physical Activity (PLAYCE) cohort study were used (analysis n = 1217). Physical activity and sedentary time were measured by accelerometry at ages two to five (preschool, wave 1) and ages five to seven (commenced full-time school, wave 2). Accelerometer data were processed using a validated machine-learning physical activity classification model. Daily time spent in sedentary behaviour, energetic play (moderate-to-vigorous physical activity (MVPA)), total physical activity, and meeting physical activity guidelines were analysed using linear and generalised linear mixed-effects models with age by sex interaction terms.
Results: All movement behaviours changed significantly with increasing age, and trends were similar in boys and girls. Total daily physical activity increased from age two to five then declined to age seven. Mean daily total physical activity exceeded 180 min/day from ages two to five. Daily energetic play increased significantly from age two to seven, however, was below 60 min/day at all ages except for seven-year-old boys. Daily sedentary time decreased to age five then increased to age seven but remained lower than at age two. All two-year-olds met their age-specific physical activity guideline, decreasing to 5% of girls and 6% of boys at age four. At age seven, 46% of boys and 35% of girls met their age-specific physical activity guideline.
Conclusions: Young children's energetic play and total physical activity increased with age, but few children aged three to seven met the energetic play (MVPA) guideline. Interventions should focus on increasing children's energetic play in early childhood. Clearer guidance and strategies are needed to support young children as they change developmentally and as they transition from one age-specific movement guideline to the next.
Background: Breastfeeding self-efficacy is a woman's self-belief and confidence in her perceived ability to breastfeed. This modifiable determinant is strongly associated with breastfeeding initiation, exclusivity, and duration. It is unclear how important the timing of breastfeeding self-efficacy measurement and interventions are. The prenatal period appears underexplored in the literature and yet a prenatal focus provides increased opportunity for breastfeeding self-efficacy enhancement and further potential improvement in breastfeeding outcomes. This scoping review aims to synthesise the evidence on prenatal breastfeeding self-efficacy, describing for the first time the theoretical frameworks, measurement tools, and interventions used in the prenatal period.
Methods: 8 databases were searched using the PCC framework (Problem: breastfeeding, Concept: self-efficacy, Context: prenatal period). From 4,667 citations and 156 additional sources identified through grey literature and snowballing, data were extracted from 184 studies and 2 guidance documents. All were summarised descriptively and narratively.
Results: Just over half (57%) of included studies stated their theoretical underpinning, with Bandura's Self-Efficacy Theory / Dennis' Breastfeeding Self-Efficacy Framework predominant. Only half of intervention studies incorporated theory in their design. More intervention studies were undertaken in the past decade than previously, but the level of theoretical underpinning has not improved. Prenatal interventions incorporating theory-led design and using components addressing the breadth of theory, more frequently reported improving breastfeeding self-efficacy and breastfeeding outcomes than those not theory-led. Intervention components used less frequently were vicarious or kinaesthetic learning (52.5%) and involvement of social circle support (26%). The Breastfeeding Self-Efficacy Scales were the most common measurement tool, despite being designed for postpartum use. Overall, issues were identified with the late prenatal timing of breastfeeding self-efficacy investigation and the design, content and phraseology of measurements and interventions used in the prenatal period.
Conclusion: This review provides novel insights for consideration in the design and conduct of breastfeeding self-efficacy studies in the prenatal period. Future research should aim to be theory-led, commence earlier in pregnancy, and embed the breadth of self-efficacy theory into the design of interventions and measurement tools. This would provide more robust data on prenatal breastfeeding self-efficacy's role in impacting breastfeeding outcomes.
Background: Accurate and feasible assessment of dietary intake remains challenging for research and healthcare. Experience Sampling Methodology (ESM) is a real-time real-life data capturing method with low burden and good feasibility not yet fully explored as alternative dietary assessment method.
Methods: This scoping review is the first to explore the implementation of ESM as an alternative to traditional dietary assessment methods by mapping the methodological considerations to apply ESM and formulating recommendations to develop an Experience Sampling-based Dietary Assessment Method (ESDAM). The scoping review methodology framework was followed by searching PubMed (including OVID) and Web of Science from 2012 until 2024.
Results: Screening of 646 articles resulted in 39 included articles describing 24 studies. ESM was mostly applied for qualitative dietary assessment (i.e. type of consumed foods) (n = 12), next to semi-quantitative dietary assessment (i.e. frequency of consumption, no portion size) (n = 7), and quantitative dietary assessment (i.e. type and portion size of consumed foods) (n = 5). Most studies used ESM to assess the intake of selected foods. Two studies applied ESM as an alternative to traditional dietary assessment methods assessing total dietary intake quantitatively (i.e. all food groups). ESM duration ranged from 4 to 30 days and most studies applied ESM for 7 days (n = 15). Sampling schedules were mostly semi-random (n = 12) or fixed (n = 9) with prompts starting at 8-10 AM and ending at 8-12 PM. ESM questionnaires were adapted from existing questionnaires, based on food consumption data or focus group discussions, and respond options were mostly presented as multiple-choice. Recall period to report dietary intake in ESM prompts varied from 15 min to 3.5 h.
Conclusions: Most studies used ESM for 7 days with fixed or semi-random sampling during waking hours and 2-h recall periods. An ESDAM can be developed starting from a food record approach (actual intake) or a validated food frequency questionnaire (long-term or habitual intake). Actual dietary intake can be measured by ESM through short intensive fixed sampling schedules while habitual dietary intake measurement by ESM allows for longer less frequent semi-random sampling schedules. ESM sampling protocols should be developed carefully to optimize feasibility and accuracy of dietary data.
Background: Mobile Ecological Momentary Assessment (EMA) is increasingly used to gather intensive, longitudinal data on behavioral nutrition, physical activity and sedentary behavior and their underlying determinants. However, a relevant concern is the risk of non-random non-compliance with mobile EMA protocols, especially in older adults. This study aimed to examine older adults' compliance with mobile EMA in health behavior studies according to participant characteristics, and prompt timing, and to provide recommendations for future EMA research.
Methods: Data of four intensive longitudinal observational studies employing mobile EMA to understand health behavior, involving 271 community-dwelling older adults (M = 71.8 years, SD = 6.8; 52% female) in Flanders, were pooled. EMA questionnaires were prompted by a smartphone application during specific time slots or events. Data on compliance (i.e. information whether a participant answered at least one item following the prompt), time slot (morning, afternoon or evening) and day (week or weekend day) of each prompt were extracted from the EMA applications. Participant characteristics, including demographics, body mass index, and smartphone ownership, were collected via self-report. Descriptive statistics of compliance were computed, and logistic mixed models were run to examine inter- and intrapersonal variability in compliance.
Results: EMA compliance averaged 77.5%, varying from 70.0 to 86.1% across studies. Compliance differed among subgroups and throughout the day. Age was associated with lower compliance (OR = 0.96, 95%CI = 0.93-0.99), while marital/cohabiting status and smartphone ownership were associated with higher compliance (OR = 1.83, 95%CI = 1.21-2.77, and OR = 4.43, 95%CI = 2.22-8.83, respectively). Compliance was lower in the evening than in the morning (OR = 0.82, 95%CI = 0.69-0.97), indicating non-random patterns that could impact study validity.
Conclusions: The findings of this study shed light on the complexities surrounding compliance with mobile EMA protocols among older adults in health behavior studies. Our analysis revealed that non-compliance within our pooled dataset was not completely random. This non-randomness could introduce bias into study findings, potentially compromising the validity of research findings. To address these challenges, we recommend adopting tailored approaches that take into account individual characteristics and temporal dynamics. Additionally, the utilization of Directed Acyclic Graphs, and advanced statistical techniques can help mitigate the impact of non-compliance on study validity.
Background: Teachers are recognized as 'key agents' for the delivery of physical activity programs and policies in schools. The aim of our study was to develop and evaluate a tool to assess teachers' capability, opportunity, and motivation to deliver school-based physical activity interventions.
Methods: The development and evaluation of the Capability, Opportunity, and Motivation to deliver Physical Activity in School Scale (COM-PASS) involved three phases. In Phase 1, we invited academic experts to participate in a Delphi study to rate, provide recommendations, and achieve consensus on questionnaire items that were based on the Capability, Opportunity, and Motivation Behavior (COM-B) model. Each item was ranked on the degree to which it matched the content of the COM-B model, using a 5-point scale ranging from '1 = Poor match' to '5 = Excellent match'. In Phase 2, we interviewed primary and secondary school teachers using a 'think-aloud' approach to assess their understanding of the items. In Phase 3, teachers (n = 196) completed the COM-PASS to assess structural validity using confirmatory factor analysis (CFA).
Results: Thirty-eight academic experts from 14 countries completed three rounds of the Delphi study. In the first round, items had an average rating score of 4.04, in the second round 4.51, and in the third (final) round 4.78. The final tool included 14 items, which related to the six constructs of the COM-B model: physical capability, psychological capability, physical opportunity, social opportunity, reflective motivation, and automatic motivation. In Phase 2, ten teachers shared their interpretation of COM-PASS via a 20-min interview, which resulted in minor changes. In Phase 3, CFA of the 3-factor model (i.e., capability, opportunity, and motivation) revealed an adequate fit to the data (χ2 = 122.6, p < .001, CFI = .945, TLI = .924, RMSEA = .066). The internal consistencies of the three subscale scores were acceptable (i.e., capability: α = .75, opportunity: α = .75, motivation: α = .81).
Conclusion: COM-PASS is a valid and reliable tool for assessing teachers' capability, opportunity, and motivation to deliver physical activity interventions in schools. Further studies examining additional psychometric properties of the COM-PASS are warranted.
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