The role of socio-demographic factors and physical functioning in the intra- and interpersonal variability of older adults' sedentary time: an observational two-country study.

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%women) 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, men, lived in Hong Kong, and experienced a lower level of physical functioning were more 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 gender, educational attainment, age, physical functioning and/or geographical location. No significant differences were detected between week and weekend day sedentary time. CONCLUSIONS: The oldest old, men, and those with functional limitations are important target groups for sedentary behavior interventions. As sedentary time was the highest in the evening future sedentary behavior intervention should pay particular attention to the evening hours. 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.

Sex-specific typologies of older adults' sedentary behaviors and their associations with health-related and socio-demographic factors: a latent profile analysis.

BACKGROUND: Some types of sedentary behaviors tend to cluster in individuals or groups of older adults. Insight into how these different types of sedentary behavior cluster is needed, as recent research suggests that not all types of sedentary behavior may have the same negative effects on physical and mental health. Therefore, the aim of this study was to identify sex-specific typologies of older adults' sedentary behavior, and to examine their associations with health-related and socio-demographic factors. METHODS: Cross-sectional data were collected as part of the BEPAS Seniors, and the Busschaert study among 696 Flemish older adults (60+). Typologies of self-reported sedentary behavior were identified using latent profile analysis, and associations with health-related and sociodemographic factors were examined using analyses of variances. RESULTS: Five distinct typologies were identified from seven sedentary behaviors (television time, computer time, transport-related sitting time, sitting for reading, sitting for hobbies, sitting for socializing and sitting for meals) in men, and three typologies were identified from six sedentary behaviors (television time, transport-related sitting time, sitting for reading, sitting for hobbies, sitting for socializing and sitting for meals) in women. Typologies that are characterized by high television time seem to be related to more negative health outcomes, like a higher BMI, less grip strength, and a lower physical and mental health-related quality-of-life. Typologies that are represented by high computer time and motorized transport seem to be related to more positive health outcomes, such as a lower body mass index, more grip strength and a higher physical and mental health-related quality-of-life. CONCLUSIONS: Although causal direction between identified typologies and health outcomes remains uncertain, our results suggests that future interventions should better focus on specific types of sedentary behavior (e.g. television time), or patterns of sedentary behavior, rather than on total sedentary behavior.

Neighbourhood drivability: environmental and individual characteristics associated with car use across Europe.

BACKGROUND: Car driving is a form of passive transportation associated with higher sedentary behaviour, which is associated with morbidity. The decision to drive a car is likely to be influenced by the 'drivability' of the built environment, but there is lack of scientific evidence regarding the relative contribution of environmental characteristics of car driving in Europe, compared to individual characteristics. This study aimed to determine which neighbourhood- and individual-level characteristics were associated with car driving in adults of five urban areas across Europe. Second, the study aimed to determine the percentage of variance in car driving explained by individual- and neighbourhood-level characteristics. METHODS: Neighbourhood environment characteristics potentially related to car use were identified from the literature. These characteristics were subsequently assessed using a Google Street View audit and available GIS databases, in 59 administrative residential neighbourhoods in five European urban areas. Car driving (min/week) and individual level characteristics were self-reported by study participants (analytic sample n = 4258). We used linear multilevel regression analyses to assess cross-sectional associations of individual and neighbourhood-level characteristics with weekly minutes of car driving, and assessed explained variance at each level and for the total model. RESULTS: Higher residential density (ß:-2.61, 95%CI: - 4.99; -0.22) and higher land-use mix (ß:-3.73, 95%CI: - 5.61; -1.86) were significantly associated with fewer weekly minutes of car driving. At the individual level, higher age (ß: 1.47, 95%CI: 0.60; 2.33), male sex (ß: 43.2, 95%CI:24.7; 61.7), being employed (ß:80.1, 95%CI: 53.6; 106.5) and ≥ 3 person household composition (ß: 47.4, 95%CI: 20.6; 74.2) were associated with higher weekly minutes of car driving. Individual and neighbourhood characteristics contributed about equally to explained variance in minutes of weekly car driving, with 2 and 3% respectively, but total explained variance remained low. CONCLUSIONS: Residential density and land-use mix were neighbourhood characteristics consistently associated with minutes of weekly car driving, besides age, sex, employment and household composition. Although total explained variance was low, both individual- and neighbourhood-level characteristics were similarly important in their associations with car use in five European urban areas. This study suggests that more, higher quality, and longitudinal data are needed to increase our understanding of car use and its effects on determinants of health.

Effectiveness of interventions using self-monitoring to reduce sedentary behavior in adults: a systematic review and meta-analysis.

BACKGROUND: Sedentary behavior occurs largely subconsciously, and thus specific behavior change techniques are needed to increase conscious awareness of sedentary behavior. Chief amongst these behavior change techniques is self-monitoring of sedentary behavior. The aim of this systematic review and meta-analysis was to evaluate the short-term effectiveness of existing interventions using self-monitoring to reduce sedentary behavior in adults. METHODS: Four electronic databases (PubMed, Embase, Web of Science, and The Cochrane Library) and grey literature (Google Scholar and the International Clinical Trials Registry Platform) were searched to identify appropriate intervention studies. Only (cluster-)randomized controlled trials that 1) assessed the short-term effectiveness of an intervention aimed at the reduction of sedentary behavior, 2) used self-monitoring as a behavior change technique, and 3) were conducted in a sample of adults with an average age ≥ 18 years, were eligible for inclusion. Relevant data were extracted, and Hedge's g was used as the measure of effect sizes. Random effects models were performed to conduct the meta-analysis. RESULTS: Nineteen intervention studies with a total of 2800 participants met the inclusion criteria. Results of the meta-analyses showed that interventions using self-monitoring significantly reduced total sedentary time (Hedges g = 0,32; 95% CI = 0,14 - 0,50; p = 0,001) and occupational sedentary time (Hedge's g = 0,56; 95% CI = 0,07 - 0,90; p = 0,02) on the short term. Subgroup analyses showed that significant intervention effects were only found if objective self-monitoring tools were used (g = 0,40; 95% CI = 0,19 - 0,60; p < 0,001), and if the intervention only targeted sedentary behavior (g = 0,45; 95% CI = 0,15-0,75; p = 0,004). No significant intervention effects were found on the number of breaks in sedentary behavior. CONCLUSIONS: Despite the small sample sizes, and the large heterogeneity, results of the current meta-analysis suggested that interventions using self-monitoring as a behavior change technique have the potential to reduce sedentary behavior in adults. If future - preferably large-scale studies - can prove that the reductions in sedentary behavior are attributable to self-monitoring and can confirm the sustainability of this behavior change, multi-level interventions including self-monitoring may impact public health by reducing sedentary behavior.

What factors explain socioeconomic inequalities in adults' television-related sitting time?

BACKGROUND: There are considerable socioeconomic inequalities in television-related sitting time, but there is little evidence for the explanatory mechanisms. We used a cohort of Belgian adults (25-60 years) and older adults (≥65 years) to examine the social cognitive, home environmental and health-related factors contributing to socioeconomic differences in television-related sitting. METHODS: We included 301 adults and 258 older adults (total n = 559). Linear regression analyses were used to examine the associations of education and occupational status with television-related sitting time, adjusted for age and gender. We assessed the explanatory power of social cognitive, home environmental and health-related factors using the traditional 'change-in-estimation method'. RESULTS: Those with low and medium education, respectively, engaged in 54 and 28 minutes per day more television-related sitting time than those with high education. We found no association between occupational status and television-related sitting time. Social cognitive factors explained 54% of the difference in television-related sitting time between those with low and high education, while home environmental factors only explained 6%, and health-related variables explained 10% of these differences. CONCLUSION: We found no occupational inequalities in television-related sitting time. Social cognitive variables such as attitude and modelling of the partner explained a large part of the educational inequalities in television-related sitting time. If confirmed by future studies, a focus on social cognition may help reduce sedentary behaviours in low-educated adults and diminish inequalities in sedentary behaviours.

Efficacy of a Self-Regulation-Based Electronic and Mobile Health Intervention Targeting an Active Lifestyle in Adults Having Type 2 Diabetes and in Adults Aged 50 Years or Older: Two Randomized Controlled Trials.

BACKGROUND: Adopting an active lifestyle plays a key role in the prevention and management of chronic diseases such as type 2 diabetes mellitus (T2DM). Web-based interventions are able to alter health behaviors and show stronger effects when they are informed by a behavior change theory. MyPlan 2.0 is a fully automated electronic health (eHealth) and mobile health (mHealth) intervention targeting physical activity (PA) and sedentary behavior (SB) based on the Health Action Process Approach (HAPA). OBJECTIVE: This study aimed to test the short-term effect of MyPlan 2.0 in altering levels of PA and SB and in changing personal determinants of behavior in adults with T2DM and in adults aged ≥50 years. METHODS: The study comprised two randomized controlled trials (RCTs) with an identical design. RCT 1 was conducted with adults with T2DM. RCT 2 was performed in adults aged ≥50 years. Data were collected via face-to-face assessments. The participants decided either to increase their level of PA or to decrease their level of SB. The participants were randomly allocated with a 2:1 ratio to the intervention group or the waiting-list control group. They were not blinded for their group allocation. The participants in the intervention group were instructed to go through MyPlan 2.0, comprising 5 sessions with an interval of 1 week between each session. The primary outcomes were objectively measured and self-reported PA (ie, light PA, moderate-to-vigorous PA, total PA, number of steps, and domain-specific [eg, transport-related] PA) and SB (ie, sitting time, number of breaks from sitting time, and length of sitting bouts). Secondary outcomes were self-reported behavioral determinants for PA and SB (eg, self-efficacy). Separate linear mixed models were performed to analyze the effects of MyPlan 2.0 in the two samples. RESULTS: In RCT 1 (n=54), the PA intervention group showed, in contrast to the control group, a decrease in self-reported time spent sitting (P=.09) and an increase in accelerometer-measured moderate (P=.05) and moderate-to-vigorous PA (P=.049). The SB intervention group displayed an increase in accelerometer-assessed breaks from sedentary time in comparison with the control group (P=.005). A total of 14 participants of RCT 1 dropped out. In RCT 2 (n=63), the PA intervention group showed an increase for self-reported total PA in comparison with the control group (P=.003). Furthermore, in contrast to the control group, the SB intervention group decreased their self-reported time spent sitting (P=.08) and increased their accelerometer-assessed moderate (P=.06) and moderate-to-vigorous PA (P=.07). A total of 8 participants of RCT 2 dropped out. CONCLUSIONS: For both the samples, the HAPA-based eHealth and mHealth intervention, MyPlan 2.0, was able to improve only some of the primary outcomes. TRIAL REGISTRATION: ClinicalTrials.gov NCT03291171; http://clinicaltrials.gov/ct2/show/NCT03291171. ClinicalTrials.gov NCT03799146; http://clinicaltrials.gov/ct2/show/NCT03799146. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/12413.

Spatial access to restaurants and grocery stores in relation to frequency of home cooking.

BACKGROUND: Little is known about the relation between the neighbourhood food environment and home cooking. We explored the independent and combined associations between residential neighbourhood spatial access to restaurants and grocery stores with home cooking in European adults. METHODS: Data of 5076 participants of the SPOTLIGHT study were collected across five European countries in 2014. Food retailers were classified into grocery stores (supermarkets and local food shops) and restaurants (full-service restaurants, fast food and take-away restaurants, café/bars). We used multinomial logistic regression models to test the associations between tertiles of spatial access to restaurants and spatial to access grocery stores and the outcome 'frequency of home cooking' categorized into 0-3; 4-5; and 6-7 days/week. Additive interaction analysis was used to test the combined association between access to grocery stores and to restaurants with home cooking. RESULTS: Mean age was 52.3 years; most participants were women (55.5%) and completed higher education (53.8%). Residents with highest access to restaurants had a reduced likelihood of home cooking 6-7 days/week (vs. 0-3 days/week) (relative risk ratio (RRR) 0.42; 95%CI = 0.23-0.76) when compared with lowest access to restaurants. No association was found for spatial access to grocery stores. Additive interaction analysis showed that individuals with medium access to grocery stores and highest access to restaurants had the lowest likelihood (RRR = 0.29, 95%CI = 0.10-0.84) of cooking 6-7 days/week when compared to individuals with lowest access to restaurants and highest access to grocery stores. CONCLUSION: Greater neighbourhood spatial access to restaurants was associated with lower frequency of home cooking, largely independent of access to grocery stores.

Exploring the cross-sectional association between outdoor recreational facilities and leisure-time physical activity: the role of usage and residential self-selection.

BACKGROUND: The availability of outdoor recreational facilities is associated with increased leisure-time physical activity (PA). We investigated how much of this association is attributable to selection effects, and explored whether usage of recreational facilities was an explanatory mechanism. METHODS: We analysed data from 5199 participants in the SPOTLIGHT survey residing in five European urban regions. Adults completed a survey and a Google Street View-based virtual audit was conducted to objectively measure the availability of outdoor recreational facilities in the residential neighbourhood. We used negative binomial GEE models to examine the association between objective and subjective availability of outdoor recreational facilities and leisure-time PA, and explored whether this association was attenuated after adjustment for socioeconomic status and preference for neighbourhoods with recreational facilities (as indicators of self-selection). We examined whether reported use of recreational facilities was associated with leisure-time PA (as explanatory mechanism), and summarized the most important motivations for (not) using recreational facilities. RESULTS: Subjective - but not objective - availability of outdoor recreational facilities was associated with higher levels of total leisure-time PA. After adjustment for self-selection (which attenuated the association by 25%), we found a 25% difference in weekly minutes of total leisure-time PA between individuals with and without self-reported availability of outdoor recreational facilities. For our study population, this translates to about 28 min per week. Participants who reported outdoor recreational facilities to be present but indicated not to use them (RR = 1.19, 95% CI = 1.03;1.22), and those reporting outdoor recreational facilities to be present and to use them (RR = 1.33, 95% CI = 1.22, 1.45) had higher levels of total leisure-time PA than those who reported outdoor recreational facilities not to be present. Proximity to outdoor recreational facilities was the most important motivation for use. CONCLUSION: The modest attenuation in the association between availability of outdoor recreational facilities and self-reported leisure-time PA suggests that individuals' higher activity levels may be due more to the perceived availability of outdoor recreational facilities than to self-selection. The use of these facilities seemed to be an important underlying mechanism, and proximity was the main motivator for using recreational facilities.

Lack of interest in physical activity - individual and environmental attributes in adults across Europe: The SPOTLIGHT project.

A considerable proportion of European adults report little or no interest in physical activity. Identifying individual-level and environmental-level characteristics of these individuals can help designing effective interventions and policies to promote physical activity. This cross-sectional study additionally explored associations between level of interest and physical activity, after controlling for other individual and environmental variables. Measures of objective and perceived features of the physical environment of residence, self-reported physical activity and other lifestyle behaviors, barriers towards physical activity, general health, and demographics were obtained from 5205 European adults participating in the 2014 online SPOTLIGHT survey. t-Tests, chi-square tests, and generalized estimating equations with negative binomial log-link function were conducted. Adults not interested in physical activity reported a higher BMI and a lower self-rated health, were less educated, and to a smaller extent female and less frequently employed. They were more prone to have less healthy eating habits, and to perceive more barriers towards physical activity. Only minor differences were observed in environmental attributes: the non-interested were slightly more likely to live in neighborhoods objectively characterized as less aesthetic and containing more destinations, and perceived as less functional, safe, and aesthetic. Even after controlling for other individual and environmental factors, interest in physical activity remained a significant correlate of physical activity, supporting the importance of this association. This study is among the first to describe characteristics of individuals with reduced interest in physical activity, suggesting that (lack of) interest is a robust correlate of physical activity in several personal and environmental conditions.

Objectively measured physical environmental neighbourhood factors are not associated with accelerometer-determined total sedentary time in adults.

BACKGROUND: The physical neighbourhood environment may influence adults' sedentary behaviour. Yet, most studies examining the association between the physical neighbourhood environment and sedentary behaviour rely on self-reported data of either the physical neighbourhood environment and/or sedentary behaviour. The aim of this study was to investigate the associations between objectively measured physical environmental neighbourhood factors and accelerometer-determined total sedentary time in adults. METHODS: In total, 219 Dutch and 128 Belgian adults (mean age ± SD: 55.8 ± 15.4 years) were recruited between March and August 2014 as part of the European SPOTLIGHT project. Physical environmental neighbourhood factors, grouped into eight domains, i.e. walking, cycling, public transport, aesthetics, land use mix, grocery stores, food outlets and recreational facilities, were assessed using the SPOTLIGHT Virtual Audit Tool. Sedentary time was collected using ActiGraph GT3X+ accelerometers. General linear mixed models were conducted to examine associations between physical environmental neighbourhood factors and total sedentary time. RESULTS: Participants were sedentary, on average, for 542.9 min/day (SD: 84.3), or 9.1 h/day. None of the examined physical environmental neighbourhood factors were significantly related to total sedentary time. CONCLUSIONS: Our findings do not support associations of objectively measured physical environmental neighbourhood factors with adults' objectively sedentary time in Dutch and Belgian adults. More research on sedentary behaviours in settings such as the home and work setting is needed to examine the influence of more specific physical environmental factors on these context-specific sedentary behaviours.

Exploring the mediating role of energy balance-related behaviours in the association between sleep duration and obesity in European adults. The SPOTLIGHT project.

Sleep restriction is a risk factor for weight gain and obesity. Few studies have formally investigated the mediating role of energy balance-related behaviours in the sleep - obesity association. The aim of this study was to explore the mediating role of physical activity, sedentary behaviours and dietary habits in the association of sleep duration with obesity in adults in five European urban regions. Data on self-reported sleep duration, energy balance-related behaviours, height and weight and other covariates were collected between February and September 2014 from participants to the SPOTLIGHT survey (N=5900, mean age 52years). Participants were recruited from 60 urban neighbourhoods in Belgium, France, Hungary, the Netherlands and the United Kingdom. Multilevel logistic regression analyses were used to assess the associations of sleep duration, energy balance-related behaviours and obesity and mediating effects were calculated using MacKinnon's product-of-coefficients method. Results indicated that a 1h increase in sleeping time was associated with a 14% lower likelihood of being obese (OR=0.86, 95%CI=0.80; 0.93). Only work-related sedentary behaviour was identified as a statistically significant mediator in the association between sleep duration and obesity for the total sample, and youngest and oldest age group. We did not find evidence for a mediating role of dietary habits and physical activities.

The mediating role of social capital in the association between neighbourhood income inequality and body mass index.

Background: Neighbourhood income inequality may contribute to differences in body weight. We explored whether neighbourhood social capital mediated the association of neighbourhood income inequality with individual body mass index (BMI). Methods: A total of 4126 adult participants from 48 neighbourhoods in France, Hungary, the Netherlands and the UK provided information on their levels of income, perceptions of neighbourhood social capital and BMI. Factor analysis of the 13-item social capital scale revealed two social capital constructs: social networks and social cohesion. Neighbourhood income inequality was defined as the ratio of the amount of income earned by the top 20% and the bottom 20% in a given neighbourhood. Two single mediation analyses-using multilevel linear regression analyses-with neighbourhood social networks and neighbourhood social cohesion as possible mediators-were conducted using MacKinnon's product-of-coefficients method, adjusted for age, gender, education and absolute household income. Results: Higher neighbourhood income inequality was associated with elevated levels of BMI and lower levels of neighbourhood social networks and neighbourhood social cohesion. High levels of neighbourhood social networks were associated with lower BMI. Results stratified by country demonstrate that social networks fully explained the association between income inequality and BMI in France and the Netherlands. Social cohesion was only a significant mediating variable for Dutch participants. Conclusion: The results suggest that in some European urban regions, neighbourhood social capital plays a large role in the association between neighbourhood income inequality and individual BMI.

Lifestyle correlates of overweight in adults: a hierarchical approach (the SPOTLIGHT project).

BACKGROUND: Obesity-related lifestyle behaviors usually co-exist but few studies have examined their simultaneous relation with body weight. This study aimed to identify the hierarchy of lifestyle-related behaviors associated with being overweight in adults, and to examine subgroups so identified. METHODS: Data were obtained from a cross-sectional survey conducted across 60 urban neighborhoods in 5 European urban regions between February and September 2014. Data on socio-demographics, physical activity, sedentary behaviors, eating habits, smoking, alcohol consumption, and sleep duration were collected by questionnaire. Participants also reported their weight and height. A recursive partitioning tree approach (CART) was applied to identify both main correlates of overweight and lifestyle subgroups. RESULTS: In 5295 adults, mean (SD) body mass index (BMI) was 25.2 (4.5) kg/m2, and 46.0 % were overweight (BMI ≥25 kg/m2). CART analysis showed that among all lifestyle-related behaviors examined, the first identified correlate was sitting time while watching television, followed by smoking status. Different combinations of lifestyle-related behaviors (prolonged daily television viewing, former smoking, short sleep, lower vegetable consumption, and lower physical activity) were associated with a higher likelihood of being overweight, revealing 10 subgroups. Members of four subgroups with overweight prevalence >50 % were mainly males, older adults, with lower education, and living in greener neighborhoods with low residential density. CONCLUSION: Sedentary behavior while watching television was identified as the most important correlate of being overweight. Delineating the hierarchy of correlates provides a better understanding of lifestyle-related behavior combinations which may assist in targeting preventative strategies aimed at tackling obesity.

Mediating role of energy-balance related behaviors in the association of neighborhood socio-economic status and residential area density with BMI: The SPOTLIGHT study.

OBJECTIVES: This study aimed to examine the mediating effects of energy-balance related behaviors on the association of neighborhood socio-economic status (SES) and neighborhood residential area density (RAD) with body mass index (BMI). METHODS: In total, 6037 adults from four neighborhood types (high SES/high RAD, high SES/low RAD, low SES/high RAD, and low SES/low RAD) in five Mid-European urban regions completed an online survey asking about their energy-balance related behaviors (physical activity [PA], sedentary behavior, and dietary behavior), determinants of these behaviors and their body weight and height. MacKinnon's product-of-coefficients test was used to assess mediating effects. RESULTS: Transport-related PA, leisure-time PA and vegetable intake seemed to mediate the association between neighborhood type and BMI. Residents from low SES/low RAD neighborhoods reported less transport-related PA, less leisure-time PA and less vegetable intake than high SES/high RAD residents, and these behaviors (i.e. transport-related PA, leisure-time PA and vegetable intake) were related to having a higher BMI. CONCLUSION: The association between neighborhood type and BMI can be explained, at least in part, by energy-balance related behaviors.

The associations between domain-specific sedentary behaviours and dietary habits in European adults: a cross-sectional analysis of the SPOTLIGHT survey.

BACKGROUND: Sedentary behaviour has been associated with obesity and related chronic diseases. Disentangling the nature of this association is complicated due to interactions with other lifestyle factors, such as dietary habits, yet limited research has investigated the relation between domain-specific sedentary behaviours and dietary habits in adults. The aim of this paper was to examine the association between domain-specific sedentary behaviours and dietary habits in adults and to test the moderating effect of age and gender on this association. METHODS: A total of 6,037 participants from five urban regions in Europe completed an online survey, of which 6,001 were included in the analyses. Multilevel mixed-effects logistic regression analyses were used to examine main associations and interaction effects. RESULTS: All domain-specific sedentary behaviours, except transport-related sitting time, were significantly related to dietary habits. In general, having a higher sitting time was related to having less healthy dietary habits, especially for television viewing. Gender did not moderate any of the relations, and age was only a significant moderator in the relation between other leisure sitting time and alcohol consumption. CONCLUSION: Domain-specific sitting behaviours were related to unhealthy dietary behaviours. However, the small effect sizes suggest that individual level behavioural interventions focusing on sedentary behaviour will not be sufficient to improve dietary habits. The fact that almost none of the associations were moderated by age or gender suggests that these associations, and possibly also the effects of interventions targeting both behaviours, may hold across age and gender groups.

Do sedentary behaviors mediate associations between socio-demographic characteristics and BMI in women living in socio-economically disadvantaged neighborhoods?

BACKGROUND: Women living in deprived neighborhoods are a risk group for overweight and obesity, particularly during the childbearing years. Several socio-demographic characteristics may compound this risk, but little is known about why this might be the case. Sedentary behaviors are emerging as a socio-demographically patterned risk factor for obesity. The purpose of the present study was to assess socio-demographic differences in sedentary behaviors, and to examine whether these behaviors could explain the relation between socio-demographic variables and BMI (BMI) in this risk group. METHODS: Women aged 18-46 years were recruited from 40 urban and 40 rural deprived neighborhoods in Victoria, Australia. In total, 3879 women reported socio-demographic variables (age, educational level, employment status, marital status, number of children, residential location and country of birth), sedentary behaviors (television time, computer time, total screen time and total sedentary time), physical activity, and height and weight, which were used to calculate BMI. For each socio-demographic variable, four single mediation models were conducted using two-level mixed-models regression analyses. Mediating effects were examined using the MacKinnon product-of-coefficients procedure and the Sobel test. RESULTS: All socio-demographic variables were significantly associated with sedentary behaviors. Single mediation analyses revealed that television time (αß = 0.017, 95% CI = 0.000, 0.030) and total screen time (αß = 0.006, 95% CI = 0.000, 0.012) mediated 14.1% and 4.9% of the relationship between educational level and BMI, respectively. Total screen time mediated 45.1% of the relationship between employment status and BMI (αß = -0.020, 95% CI = -0.033, -0.006), and television time mediated 8.2% of the relationship between country of birth and BMI (αß = -0.008, 95% CI = -0.016, -0.001). CONCLUSION: Sedentary behaviors differed depending on socio-demographic characteristics, and partly explained the relationship between socio-demographic factors and BMI in this sample of women. Both television time and total screen time are potential behaviors to target in future programs aimed at reducing socio-demographic disparities in overweight and obesity.

Educational differences in the validity of self-reported physical activity.

BACKGROUND: The assessment of physical activity for surveillance or population based studies is usually done with self-report questionnaires. However, bias in self-reported physical activity may be greater in lower educated than in higher educated populations. The aim of the present study is to describe educational differences in the validity of self-reported physical activity. METHODS: We included 196 healthy adults (age 57 ± 15.4, of whom 17% low, 24% medium and 59% high educated). Criterion validity of an adapted International Physical Activity Questionnaire was assessed against the ActiGraph GT3X+ accelerometer. RESULTS: While criterion validity of self-reported physical activity was low to moderate in the total sample (Spearman rho ranged from 0.16 to 0.27, depending on the variables used), the validity in lower educated respondents was poor (-0.07 to 0.05). CONCLUSIONS: The results confirm the hypothesis that self-report physical activity questionnaires are less valid in lower educated populations.

Effectiveness of a web-based, computer-tailored, pedometer-based physical activity intervention for adults: a cluster randomized controlled trial.

BACKGROUND: Computer-tailored physical activity (PA) interventions delivered through the Internet represent a promising and appealing method to promote PA at a population level. However, personalized advice is mostly provided based on subjectively measured PA, which is not very accurate and might result in the delivery of advice that is not credible or effective. Therefore, an innovative computer-tailored PA advice was developed, based on objectively pedometer-measured PA. OBJECTIVE: The study aim was to evaluate the effectiveness of a computer-tailored, pedometer-based PA intervention in working adults. METHODS: Participants (≥18 years) were recruited between May and December 2012 from eight Flemish workplaces. These workplaces were allocated randomly to an intervention or control group. Intervention group participants (n=137) received (1) a booklet with information on how to increase their steps, (2) a non-blinded pedometer, and (3) an Internet link to request computer-tailored step advice. Control group participants (n=137) did not receive any of the intervention components. Self-reported and pedometer-based PA were assessed at baseline (T0), and 1 month (T1) and 3 months (T2) months post baseline. Repeated measures analyses of covariance were used to examine intervention effects for both the total sample and the at-risk sample (ie, adults not reaching 10,000 steps a day at baseline). RESULTS: The recruitment process resulted in 274 respondents (response rate of 15.1%) who agreed to participate, of whom 190 (69.3%) belonged to the at-risk sample. Between T0 and T1 (1-month post baseline), significant intervention effects were found for participants' daily step counts in both the total sample (P=.004) and the at-risk sample (P=.001). In the at-risk sample, the intervention effects showed a daily step count increase of 1056 steps in the intervention group, compared to a decrease of 258 steps in the control group. Comparison of participants' self-reported PA revealed a significant intervention effect for time spent walking in the at-risk sample (P=.02). Intervention effects were still significant 3 months post baseline for participants' daily step counts in both the total sample (P=.03) and the at-risk sample (P=.02); however, self-reported PA differences were no longer significant. CONCLUSIONS: A computer-tailored, pedometer-based PA intervention was effective in increasing both pedometer-based and self-reported PA levels, mainly in the at-risk participants. However, more effort should be devoted to recruit and retain participants in order to improve the public health impact of the intervention. TRIAL REGISTRATION: ClinicalTrials.gov: NCT02080585; https://clinicaltrials.gov/ct2/show/NCT02080585 (Archived by WebCite at http://www.webcitation.org/6VvQnRQSy).

A RE-AIM evaluation of evidence-based multi-level interventions to improve obesity-related behaviours in adults: a systematic review (the SPOTLIGHT project).

BACKGROUND: This systematic literature review describes the potential public health impact of evidence-based multi-level interventions to improve obesity-related behaviours in adults, using the Reach, Efficacy, Adoption, Implementation and Maintenance (RE-AIM) framework. METHODS: Electronic databases (PubMed, Embase, and The Cochrane Library) were searched to identify intervention studies published between January 2000 and October 2013. The following inclusion criteria were used: (1) the study included at least one outcome measure assessing obesity-related behaviours (i.e. diet, physical activity or sedentary behaviour), (2) the study collected data over at least one year and (3) the study's intervention targeted adults, was conducted in a specified geographical area or worksite, and was multi-level (i.e. targeting both individual and environmental level). Evidence of RE-AIM of the selected interventions was assessed. Potential public health impact of an intervention was evaluated if information was provided on at least four of the five RE-AIM dimensions. RESULTS: Thirty-five multi-level interventions met the inclusion criteria. RE-AIM evaluation revealed that the included interventions generally had the potential to: reach a large number of people (on average 58% of the target population was aware of the intervention); achieve the assumed goals (89% found positive outcomes); be broadly adopted (the proportion of intervention deliverers varied from 9% to 92%) and be sustained (sixteen interventions were maintained). The highest potential public health impact was found in multi-level interventions that: 1) focused on all levels at the beginning of the planning process, 2) guided the implementation process using diffusion theory, and 3) used a website to disseminate the intervention. CONCLUSIONS: Although most studies underreported results within the RE-AIM dimensions, the reported Reach, Effectiveness, Adoption, Implementation and Maintenance were positively evaluated. However, more information on external validity and sustainability is needed in order to take informed decisions on the choice of interventions that should be implemented in real-world settings to accomplish long-term changes in obesity-related behaviours.

A meta-analysis of serious digital games for healthy lifestyle promotion.

Several systematic reviews have described health-promoting effects of serious games but so far no meta-analysis has been reported. This paper presents a meta-analysis of 54 serious digital game studies for healthy lifestyle promotion, in which we investigated the overall effectiveness of serious digital games on healthy lifestyle promotion outcomes and the role of theoretically and clinically important moderators. Findings showed that serious games have small positive effects on healthy lifestyles (g=0.260, 95% CI 0.148; 0.373) and their determinants (g=0.334, 95% CI 0.260; 0.407), especially for knowledge. Effects on clinical outcomes were significant, but much smaller (g=0.079, 95% CI 0.038; 0.120). Long-term effects were maintained for all outcomes except for behavior. Serious games are best individually tailored to both socio-demographic and change need information, and benefit from a strong focus on game theories or a dual theoretical foundation in both behavioral prediction and game theories. They can be effective either as a stand-alone or multi-component programs, and appeal to populations regardless of age and gender. Given that effects of games remain heterogeneous, further explorations of which game features create larger effects are needed.