Delfien Van Dyck’s research while affiliated with Ghent University and other places

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: Persons in socioeconomically disadvantaged situations (PSEDS) are generally less likely to engage in recreational walking (RW) compared to higher socioeconomic groups and are often more dependent on their local environment. Studies on RW have primarily focused on the role of the built environment for the general adult population and the older population in urban areas. The aim of this study is to qualitatively identify the perceived environmental factors affecting RW among PSEDS in peri-urban areas. Methods: In two peri-urban municipalities in Belgium, walk-along interviews were conducted until data saturation with a purposeful convenience sampling of 38 PSEDS (25-65y/o) to identify local environmental factors affecting RW. A subsample of 22 participants joined a focus group (n = 4) to categorize the identified factors into environmental types (physical, sociocultural, political, and economic) of the Analysis Grid for Environments Linked to Obesity (ANGELO) framework. The interviews were transcribed and analyzed thematically using Maxqda 2022.0. Results: The information environment (dissemination, retrieving and understanding of information) was added to the ANGELO framework, highlighting the importance of digital literacy. Availability and accessibility of well-maintained walking surfaces, toilets, street lighting and seating options (physical environment), social support, dog-ownership, stigmatization, social isolation, and a sense of belonging (sociocultural environment) and indirect costs (economic environment) were identified as important environmental factors in RW among PSEDS. The identified political and economic factors are intertwined with the other environments. Conclusions: Perceived environmental factors affect RW among PSEDS and peri-urban settings offer specific challenges. Local governments should incorporate citizen perception into decision-making processes to create supportive environments that have the potential to promote RW among PSEDS in a peri-urban setting.

Background The growing number of patients with type 2 diabetes and prediabetes is a major public health concern. Physical activity is a cornerstone of diabetes management and may prevent its onset in prediabetes patients. Despite this, many patients with (pre)diabetes remain physically inactive. Primary care physicians are well-situated to deliver interventions to increase their patients' physical activity levels. However, effective and sustainable physical activity interventions for (pre)diabetes patients that can be translated into routine primary care are lacking. Methods We describe the rationale and protocol for a 12-month pragmatic, multicentre, randomised, controlled trial assessing the effectiveness of an mHealth intervention delivered in general practice to increase physical activity and reduce sedentary behaviour of patients with prediabetes and type 2 diabetes (ENERGISED). Twenty-one general practices will recruit 340 patients with (pre)diabetes during routine health checkups. Patients allocated to the active control arm will receive a Fitbit activity tracker to self-monitor their daily steps and try to achieve the recommended step goal. Patients allocated to the intervention arm will additionally receive the mHealth intervention, including the delivery of several text messages per week, with some of them delivered just in time, based on data continuously collected by the Fitbit tracker. The trial consists of two phases, each lasting six months: the lead-in phase, when the mHealth intervention will be supported with human phone counselling, and the maintenance phase, when the intervention will be fully automated. The primary outcome, average ambulatory activity (steps/day) measured by a wrist-worn accelerometer, will be assessed at the end of the maintenance phase at 12 months. Discussion The trial has several strengths, such as the choice of active control to isolate the net effect of the intervention beyond simple self-monitoring with an activity tracker, broad eligibility criteria allowing for the inclusion of patients without a smartphone, procedures to minimise selection bias, and involvement of a relatively large number of general practices. These design choices contribute to the trial's pragmatic character and ensure that the intervention, if effective, can be translated into routine primary care practice, allowing important public health benefits. Trial registration ClinicalTrials.gov (NCT05351359, 28/04/2022).

Background Health inequalities partially remain due to differences in diet between socioeconomic groups. Examining the association between socio-ecological factors and the diet of socioeconomically disadvantaged (SED) individuals can enhance the development of interventions to decrease health inequalities. Methods In total, 278 SED adults residing in two Flemish municipalities completed a survey addressing sociodemographics, diet, health and their perceptions of the food environment. The objective food environment was examined by assessing food retailer information in street network-based buffers of 500m and 1000m around participants’ addresses. Linear regression was used to test assumptions. Results Individual factors such as poor subjective health (OR0.58;CI 0.34-0.97), food insecurity (OR0.60;CI 0.38-0.94) and living alone (OR0.86;CI 0.75-0.98) were negatively associated with healthy dietary habits such as daily fruit and vegetable (FV) consumption. Positive perceptions on the availability of FV were positively associated (OR1.09;CI 1.02-1.17) with daily FV consumption. Objective food environmental factors showed a stronger association with unhealthy dietary habits. A greater amount of retailers within 1000m walking distance was negatively associated with fast-food (OR0.96;CI 0.94-0.99) and sugar-sweetened beverages (SSB) consumption (OR0.93; CI 0.88-0.98). More supermarkets within 500m distance was negatively associated (OR0.77;CI 0.58-0.97) with SSB consumption, while more convenience stores within a 1000m distance was positively associated (OR1.48;CI 1.17-1.88) with SSB consumption. Conclusions Our findings suggest that factors associated with the diet of SED adults differ according to food and drink items. Interventions focused on this population should take these differences into account. Key messages

Background Insufficient physical activity (PA) is a risk factor for obesity and non-communicable diseases and seems more prevalent among socioeconomically disadvantaged (SED) adults. Recreational walking (RW) is an important type of leisure time PA which can be done for free and without specific equipment or facilities. Environmental factors influencing PA may be particularly important for SED adults who are more reliant on their direct environment. The objectively measured environment is not always congruent with the perception of residents, and this may differ by socioeconomic group. This study aims to identify the local environmental factors important for RW as perceived by SED adults. Methods This study is part of the CIVISANO project. Purposeful convenience sampling was used to recruit 38 SED adults (25-65 y/o) in two Flemish semi-urban municipalities. Individual walk-along interviews have been performed in the participants’ neighborhood. 20 participants joined the focus group discussion (n = 4) that were intended for member checking, to categorize identified environmental factors and to identify local actions to promote recreational walking. MaxQDA was used for content analysis. Results The way the environment is perceived by SED adults plays an important role in their RW behavior. Results demonstrate the interrelation of different environmental types (physical, sociocultural, economic, political and information) and sizes (micro, meso, macro). Improving communication and knowledge transfer, stimulation of physical, sociocultural, and economic accessibility, and promotion of physical and social safety are identified most important action points for the local government to facilitate RW. Conclusions Our findings indicate that the perceived local environment can play an important role in promoting RW among SED adults. Future studies should investigate if changes in these environments and in residents’ perception lead to changes in RW behavior of SED adults. Key messages

This study aimed to contrast the associations of street view-, land use- and satellite-derived greenspace measures with older adults' mental health and to examine the mediating effects of neighborhood environmental perceptions (i.e., noise, aesthetics and satisfaction with recreational opportunities) to explain potential heterogeneity in the associations. Data of 879 respondents aged 60 or older in Dalian, China were used, and multilevel regression models were conducted in Stata. Results indicated that the Normalized Difference Vegetation Index (NDVI), vegetation coverage, park coverage and streetscape grasses were positively correlated with older adults' mental health. The associations of exposure metrics measured by overhead view were stronger than those measured by the street view. Streetscape grasses had a stronger association with older adults' mental health than streetscape trees. Noise, aesthetics and satisfaction with recreational opportunities mediated these associations, but the strength of the mediating effects differed across the greenspace measures. Our findings confirm the necessity of multi-measures assessment for greenspace to examine associations with older adults' mental health in Chinese settings and can contribute to the realization of health benefits of urban greenspace.

Background Many theoretical frameworks have been used in order to understand health behaviors such as physical activity, sufficient sleep, healthy eating habits, etc. In most research studies, determinants within these frameworks are assessed only once and thus are considered as stable over time, which leads to rather ‘static’ health behavior change interventions. However, in real-life, individual-level determinants probably vary over time (within days and from day to day), but currently, not much is known about these time-dependent fluctuations in determinants. In order to personalize health behavior change interventions in a more dynamic manner, such information is urgently needed. Objective The purpose of this study was to explore the time-dependent variability of emotions, physical complaints, intention, and self-efficacy in older adults (65+) using Ecological Momentary Assessment (EMA). Methods Observational data were collected in 64 healthy older adults (56.3% men; mean age 72.1 ± 5.6 years) using EMA. Participants answered questions regarding emotions ( i.e. , cheerfulness, relaxation, enthusiasm, satisfaction, insecurity, anxiousness, irritation, feeling down), physical complaints ( i.e. , fatigue, pain, dizziness, stiffness, shortness of breath), intention, and self-efficacy six times a day for seven consecutive days using a smartphone-based questionnaire. Generalized linear mixed models were used to assess the fluctuations of individual determinants within subjects and over days. Results A low variability is present for the negative emotions ( i.e. , insecurity, anxiousness, irritation, feeling down) and physical complaints of dizziness and shortness of breath. The majority of the variance for relaxation, satisfaction, insecurity, anxiousness, irritation, feeling down, fatigue, dizziness, intention, and self-efficacy is explained by the within subjects and within days variance (42.9% to 65.8%). Hence, these determinants mainly differed within the same subject and within the same day. The between subjects variance explained the majority of the variance for cheerfulness, enthusiasm, pain, stiffness, and shortness of breath (50.2% to 67.3%). Hence, these determinants mainly differed between different subjects. Conclusions This study reveals that multiple individual-level determinants are time-dependent, and are better considered as ‘dynamic’ or unstable behavior determinants. This study provides us with important insights concerning the development of dynamic health behavior change interventions, anticipating real-time dynamics of determinants instead of considering determinants as stable within individuals.

Background. Insight into the variability of older adults’ sedentary time is needed to inform future interventions. The aim of this study was to examine the intra- and interpersonal variability in sedentary time, and the moderating role of socio-demographics, physical functioning and geographical location in this variability. Methods. Cross-sectional data from 818 community-dwelling older adults (mean age: 74.8 years; 61.1% female) of the Active Lifestyle and the Environment in Chinese Seniors and Belgian Environmental Physical Activity Study in Seniors were used. An interview questionnaire was administered to collect socio-demographic information. The Short Physical Performance Battery was performed to evaluate physical functioning, and Actigraph GT3X(+) accelerometers were used to estimate sedentary time. Linear mixed models with random intercepts at the neighborhood, person and day levels examined the variability in sedentary time, and the moderating role of socio-demographics, physical functioning and geographical location within this variability. Results. Most of the variance in accelerometry-assessed sedentary time was due to intrapersonal variability across periods of the day (72.4%) followed by interpersonal variability within neighborhoods (25.6%). Those who were older, male, lived in Hong Kong, and experienced a lower level of physical functioning were less sedentary than their counterparts. Sedentary time increased throughout the day, with highest levels of sedentary time observed between 6:00 and 9:00 pm. The patterns of sedentary time across times of the day differed by sex, educational attainment, age, physical functioning and/or geographical location. No significant differences were detected between week and weekend day sedentary time. Conclusions. Researchers developing interventions to encourage older adults to sit less should pay particular attention to the evening hours, if future studies can demonstrate that older adults are also receptive towards sedentary behavior interventions in the evening. The variations in diurnal patterns of sedentary time between population subgroups suggest that personalized just-in-time adaptive interventions might be a promising strategy to reduce older adults’ sedentary time.

Background The prevalence of obesity worldwide has been steadily increasing. This has generated an uptake in research determining the cause of obesity. One of the primary drivers that have been identified is the “obesogenic environment', which is an environment that contains features that increase excess weight in individuals or populations. Obesogenic environments are unevenly distributed with socio-economically disadvantaged neighbourhoods being more affected. Methods This survey is part of the CIVISANO (‘Community-based participatory research to tackle the disparities in health-enhancing lifestyle within the municipality environment') project, which will be conducted in two municipalities. Respondents will be socio-economically disadvantaged adults between 25- and 65-years old. To gain information on individual characteristics and perceptions of the obesogenic environment, residents will be invited to complete a survey. Since it is known that socio-economically disadvantaged respondents are difficult to reach a non-random active recruitment approach will be applied. The following variables are included in the survey: sociodemographic information, subjective health and anthropometrics, dietary habits, food security and physical activity. Items from the SPOTLIGHT project survey and NEMS-P survey were added to assess respondent's perceptions of features of the obesogenic environment. Additional variables on individual characteristics were based on items from the Belgian National Health Interview Survey of 2019. Results Through the survey, we expect to gain insight into the perceptions of socio-economically disadvantaged adults on obesogenic features of their local environment. Initial results from the survey will be available in the upcoming months. Conclusions The construction of instruments to assess the context-specific features, which can be compared with objective measurements, can increase our knowledge of contextual determinants of the obesogenic environment. Key messages The first Flemish survey that focuses on perceptions of socio-economically disadvantaged adults on obesogenic features of their local environment in the municipal context. Gaining a better understanding of the local obesogenic environment creates an opportunity to promote and strengthen the development of effective local interventions to build healthier environments.