Explaining differential socioeconomic effects in population health interventions: development and application of a new tool to classify intervention agentic demand.

BACKGROUND: The agentic demand of population health interventions (PHIs) might influence how interventions work. Highly agentic interventions (eg, information campaigns) rely on recipients noticing and responding to the intervention. Resources required for individuals to benefit from highly agentic interventions have a socioeconomical pattern, thus agentic demand might affect intervention effectiveness and equity. Systematic evidence exploring these associations is missing due to the absence of adequate tools to classify agentic demands. We aimed to develop such a tool and test its application. METHODS: Our iterative development process involved: (1) systematic identification of diet and physical activity PHIs; (2) coding of intervention actors and actions; (3) data synthesis; (4) expert qualitative feedback; and (5) reliability assessment. We searched nine databases for articles published between Jan 1, 2010, and Aug 17, 2020. For all included articles, we coded the actors (people required to act within an intervention) and their actions (what they were required to do for the intervention to have its intended effects). We combined these codes for similar intervention types to develop overarching schematic flow chart diagrams used to identify concepts, and we organised these into a draft tool. After expert feedback, and we assessed inter-rater reliability of the final version. We applied the final tool in a proof-of-concept review, extracting studies from three existing equity-focused systematic reviews on tool category, overall intervention effect, and differential socioeconomic effects and visualised findings. FINDINGS: We identified three concepts affecting agentic demands of intervention components: exposure, two levels (how recipients encounter the intervention); mechanism of action, five levels; and engagement, two levels (how recipients respond to the intervention). We then combined these concepts to form 20 categories that grouped together interventions with similar agentic demands. In the review, we applied the tool to 26 PHIs that included 163 components. Intervention components were concentrated in a small number of categories, and their categorisation was related to intervention equity but not to effectiveness. INTERPRETATION: We present a novel tool to classify the agentic demand of PHIs and demonstrate its feasibility within a systematic review. Linking intervention types to their effect on inequalities enables these factors to be considered when designing or selecting interventions. Users of the tool can avoid implementing intervention types that are likely to widen inequalities or implement them alongside counter-strategies to minimise any adverse equity effects. Applying this tool within future research, policy, and practice to design, select, evaluate, and synthesise evidence from PHIs has the potential to advance our understanding of how interventions work and their effect on socioeconomic inequalities. FUNDING: Public Health Policy Research Unit (PH-PRU), National Institute for Health and Care Research (NIHR) Policy Research Programme.

Effectiveness and cost-effectiveness of the GoActive intervention to increase physical activity among UK adolescents: A cluster randomised controlled trial.

BACKGROUND: Less than 20% of adolescents globally meet recommended levels of physical activity, and not meeting these recommended levels is associated with social disadvantage and rising disease risk. The determinants of physical activity in adolescents are multilevel and poorly understood, but the school's social environment likely plays an important role. We conducted a cluster randomised controlled trial to assess the effectiveness of a school-based programme (GoActive) to increase moderate-to-vigorous physical activity (MVPA) among adolescents. METHODS AND FINDINGS: Non-fee-paying, co-educational schools including Year 9 students in the UK counties of Cambridgeshire and Essex were eligible for inclusion. Within participating schools (n = 16), all Year 9 students were eligible and invited to participate. Participants were 2,862 13- to 14-year-olds (84% of eligible students). After baseline assessment, schools were computer-randomised, stratified by school-level pupil premium funding (below/above county-specific median) and county (control: 8 schools, 1,319 participants, mean [SD] participants per school n = 165 [62]; intervention: 8 schools, 1,543 participants, n = 193 [43]). Measurement staff were blinded to allocation. The iteratively developed, feasibility-tested 12-week intervention, aligned with self-determination theory, trained older adolescent mentors and in-class peer-leaders to encourage classes to conduct 2 new weekly activities. Students and classes gained points and rewards for engaging in any activity in or out of school. The primary outcome was average daily minutes of accelerometer-assessed MVPA at 10-month follow-up; a mixed-methods process evaluation evaluated implementation. Of 2,862 recruited participants (52.1% male), 2,167 (76%) attended 10-month follow-up measurements; we analysed the primary outcome for 1,874 participants (65.5%). At 10 months, there was a mean (SD) decrease in MVPA of 8.3 (19.3) minutes in the control group and 10.4 (22.7) minutes in the intervention group (baseline-adjusted difference [95% confidence interval] -1.91 minutes [-5.53 to 1.70], p = 0.316). The programme cost £13 per student compared with control; it was not cost-effective. Overall, 62.9% of students and 87.3% of mentors reported that GoActive was fun. Teachers and mentors commented that their roles in programme delivery were unclear. Implementation fidelity was low. The main methodological limitation of this study was the relatively affluent and ethnically homogeneous sample. CONCLUSIONS: In this study, we observed that a rigorously developed school-based intervention was no more effective than standard school practice at preventing declines in adolescent physical activity. Interdisciplinary research is required to understand educational-setting-specific implementation challenges. School leaders and authorities should be realistic about expectations of the effect of school-based physical activity promotion strategies implemented at scale. TRIAL REGISTRATION: ISRCTN Registry ISRCTN31583496.

Time spent on social media use and BMI z-score: A cross-sectional explanatory pathway analysis of 10798 14-year-old boys and girls.

BACKGROUND: The association between adolescent time spent on social media use and body mass index z-score (BMI z-score) is unclear. Pathways of association and sex differences are also unclear. This study examined the association between time spent on social media use and BMI z-score (primary objective) and potential explanatory pathways (secondary objective) for boys and girls. METHODS: Data are from 5332 girls and 5466 boys aged 14 years in the UK Millennium Cohort Study. BMI z-score was regressed on self-reported time spent on social media use (h/day). Potential explanatory pathways explored included dietary intake, sleep duration, depressive symptoms, cyberbullying, body-weight satisfaction, self-esteem, and well-being. Sex-stratified multivariable linear regression and structural equation modelling were used to examine potential associations and explanatory pathways. RESULTS: Using social media for ≥5 h/day (vs. <1 h/day) was positively associated with BMI z-score for girls (ß [95% CI]) (0.15 [0.06, 0.25]) (primary objective, multivariable linear regression). For girls, the direct association was attenuated when sleep duration (0.12 [0.02, 0.22]), depressive symptoms (0.12 [0.02, 0.22]), body-weight satisfaction (0.07 [-0.02, 0.16]), and well-being (0.11 [0.01, 0.20]) were included (secondary objective, structural equation modelling). No associations were observed for boys and potential explanatory pathway variables were not examined. CONCLUSIONS: In girls, high time spent on social media use (≥5 h/day) was positively associated with BMI z-score, and this association was partially explained by sleep duration, depressive symptoms, body-weight satisfaction, and well-being. Associations and attenuations between a self-reported summary variable of time spent on social media use and BMI z-score were small. Further research should examine whether time spent on social media use is related to other adolescent health metrics.

The school policy, social, and physical environment and change in adolescent physical activity: An exploratory analysis using the LASSO.

PURPOSE: We examined the association between the school policy, social and physical environment and change in adolescent physical activity (PA) and explored how sex and socioeconomic status modified potential associations. METHODS: Data from the GoActive study were used for these analyses. Participants were adolescents (n = 1765, mean age±SD 13.2±0.4y) from the East of England, UK. Change in longitudinal accelerometer assessed moderate-to-vigorous physical activity (MVPA) was the outcome. School policy, social and physical environment features (n = 267) were exposures. The least absolute shrinkage and selection operator variable selection method (LASSO) was used to determine exposures most relevant to the outcome. Exposures selected by the LASSO were added to a multiple linear regression model with estimates of change in min/day of MVPA per 1-unit change in each exposure reported. Post-hoc analyses, exploring associations between change in variables selected by the LASSO and change in MVPA, were undertaken to further explain findings. FINDINGS: No school policy or physical environment features were selected by the LASSO as predictors of change in MVPA. The LASSO selected two school social environment variables (participants asking a friend to do physical activity; friend asking a participant to do physical activity) as potential predictors of change in MVPA but no significant associations were found in subsequent linear regression models for all participants (ß [95%CI] -1.01 [-2.73;0.71] and 0.65 [-2.17;0.87] min/day respectively). In the post-hoc analyses, for every unit increase in change in participants asking a friend to do PA and change in a friend asking participants to do PA, an increase in MVPA of 2.78 (1.55;4.02) and 1.80 (0.48;3.11) min/day was predicted respectively. CONCLUSIONS: The school social environment is associated with PA during adolescence. Further exploration of how friendships during adolescence may be leveraged to support effective PA promotion in schools is warranted.

Cohabitation and marriage during the transition between adolescence and emerging adulthood: A systematic review of changes in weight-related outcomes, diet and physical activity.

Our aim was to systematically review the effect of cohabitation and marriage on physical activity, diet and weight-related outcomes during emerging adulthood. A systematic search of six electronic databases was conducted until July 2019 (PROSPERO:CRD42018106943). Prospective studies were included if data were presented for a weight-related outcome, physical activity, and/or diet among 15-35 years-old participants assessed pre- and post-cohabitation or marriage and compared to a consistently non-cohabiting/non-married (single) reference group. Following title/abstract screening, two reviewers independently screened full-text and assessed risk of bias. There were 11 studies that met inclusion criteria. Outcomes included: body mass index (BMI) only (n = 3), physical activity only (n = 4), diet only (n = 2), BMI and physical activity (n = 1), and all outcomes (n = 1). Cohabitation or marriage was associated with greater BMI increases compared to remaining single among both men and women. Three studies analysed separately cohabitation and marriage and 3 of 4 found that only marriage was associated with higher BMI. Compared to being consistently single, starting cohabitation or getting married were associated with decreased physical activity in 2 of 4 studies among men and 4 of 6 studies among women, with no differences between marriage and cohabitation. Of the three studies examining change in diet, two showed no difference between individuals beginning to cohabit compared to those remaining single; without gender differences. Starting cohabitation and getting married may be valuable targets for weight management interventions, but more studies are needed to investigate the effect of cohabitation and marriage on health behaviours.

Adolescents' perspectives on a school-based physical activity intervention: A mixed method study.

Purpose: To examine adolescent experiences and perspectives of the GoActive intervention (ISRCTN31583496) using mixed methods process evaluation to determine satisfaction with intervention components and interpret adolescents' experiences of the intervention process in order to provide insights for future intervention design. Methods: Participants (n = 1542; 13.2 ±  0.4 years, mean ± SD) provided questionnaire data at baseline (shyness, activity level) and post-intervention (intervention acceptability, satisfaction with components). Between-group differences (boys vs. girls and shy/inactive vs. others) were tested with linear regression models, accounting for school clustering. Data from 16 individual interviews (shy/inactive) and 11 focus groups with 48 participants (mean = 4; range 2-7) were thematically coded. Qualitative and quantitative data were merged in an integrative mixed methods convergence matrix, which denoted convergence and dissonance across datasets. Results: Effect sizes for quantitative results were small and may not represent substantial between-group differences. Boys (vs. girls) preferred class-based sessions (ß = 0.2, 95% confidence interval (CI): 0.1-0.3); qualitative data suggested that this was because boys preferred competition, which was supported quantitatively (ß = 0.2, 95%CI: 0.1-0.3). Shy/inactive students did not enjoy the competition (ß = -0.3, 95%CI: -0.5 to -0.1). Boys enjoyed trying new activities more (ß = 0.1, 95%CI: 0.1-0.2); qualitative data indicated a desire to try new activities across all subgroups but identified barriers to choosing unfamiliar activities with self-imposed choice restriction leading to boredom. Qualitative data highlighted critique of mentorship; adolescents liked the idea, but older mentors did not meet expectations. Conclusion: We interpreted adolescent perspectives of intervention components and implementation to provide insights into future complex interventions aimed at increasing young people's physical activity in school-based settings. The intervention component mentorship was liked in principle, but implementation issues undesirably impacted satisfaction; competition was disliked by girls and shy/inactive students. The results highlight the importance of considering gender differences in preference of competition and extensive mentorship training.

Pathways to Increasing Adolescent Physical Activity and Wellbeing: A Mediation Analysis of Intervention Components Designed Using a Participatory Approach.

We assessed which intervention components were associated with change in moderate-to-vigorous physical activity (MVPA) and wellbeing through proposed psychosocial mediators. Eight schools (n = 1319; 13-14 years) ran GoActive, where older mentors and in-class-peer-leaders encouraged classes to conduct two new activities/week; students gained points and rewards for activity. We assessed exposures: participant-perceived engagement with components (post-intervention): older mentorship, peer leadership, class sessions, competition, rewards, points entered online; potential mediators (change from baseline): social support, self-efficacy, group cohesion, friendship quality, self-esteem; and outcomes (change from baseline): accelerometer-assessed MVPA (min/day), wellbeing (Warwick-Edinburgh). Mediation was assessed using linear regression models stratified by gender (adjusted for age, ethnicity, language, school, BMI z-score, baseline values), assessing associations between (1) exposures and mediators, (2) exposures and outcomes (without mediators) and (3) exposure and mediator with outcome using bootstrap resampling. No evidence was found to support the use of these components to increase physical activity. Among boys, higher perceived teacher and mentor support were associated with improved wellbeing via various mediators. Among girls, higher perceived mentor support and perception of competition and rewards were positively associated with wellbeing via self-efficacy, self-esteem and social support. If implemented well, mentorship could increase wellbeing among adolescents. Teacher support and class-based activity sessions may be important for boys' wellbeing, whereas rewards and competition warrant consideration among girls.

Changes in physical activity, diet, and body weight across the education and employment transitions of early adulthood: A systematic review and meta-analysis.

Early adulthood is a time when individuals go through important life transitions, such as moving from high school into higher education or employment, but the impact of these life transitions on changes in body weight, diet, and physical activity is not known. We searched six electronic databases to July 2019 for longitudinal observational studies providing data on adiposity, diet, and/or physical activity across education or employment transitions in young people aged between 15 and 35 years. We found 19 studies, of which 17 assessed changes in physical activity, three body weight, and five diet or eating behaviours. Meta-analysis (n=9) found that leaving high school was associated with a decrease of -7.04 (95% CI, -11.26, -2.82) min/day of moderate-to-vigorous physical activity. Three studies reported increases in body weight on leaving high school. A small number of studies suggested decreases in diet quality on leaving high school (n=2/4 papers) and leaving university (n=1) but not on starting employment (n=1). Studies suggested no change in physical activity on leaving university (n=4) but decreases in physical activity on starting employment (n=2/3). The transition of leaving high school is an important time to support individuals to prevent decreases in physical activity and gains in body weight.

Becoming a parent: A systematic review and meta-analysis of changes in BMI, diet, and physical activity.

Obesity prevalence rises fastest during young adulthood when weight, diet, and physical activity may be influenced by life events, including becoming a parent, but the impact is uncertain. We searched six electronic databases to July 2019 for longitudinal studies (both sexes) aged 15 to 35 years with a prospective pre-pregnancy/parenthood and post-delivery outcome. Of 11 studies (across 15 papers), six studies (women only) were eligible for meta-analysis of the difference in change in body mass index (BMI; kg/m2 ) between remaining without children and becoming a parent. Mean (±SD) BMI gain for non-mothers was 2.8 ± 1.3 kg/m2 (~7.5 kg for 164-cm woman) over 5.6 ± 3.1 years; 12.3% of baseline BMI (22.8 ± 2.5 kg/m2 ). Becoming a mother was associated with an additional BMI increase of 0.47 ± 0.26 kg/m2 (~1.3 kg), 4.3% of baseline BMI (22.8 ± 5.6 kg/m2 ); the one study including men reported no difference in change. Physical activity results were equivocal; 2/4 studies (women) and 2/2 (men) showed a greater decline in parents versus non-parents; diet (three studies) varied by dietary measure, mostly indicating no difference. Becoming a mother is associated with 17% greater absolute BMI gain than remaining childless. Motherhood BMI gain is additional to an alarming BMI increase among young women, highlighting the need for obesity prevention among all young women, including mothers.

Reach, Recruitment, Dose, and Intervention Fidelity of the GoActive School-Based Physical Activity Intervention in the UK: A Mixed-Methods Process Evaluation.

School-based multi-component physical activity (PA) promotion is advocated; however, research has indicated that a multi-component approach may not always be effective at increasing adolescent PA. Evaluation of the GoActive 12-week multi-component school-based intervention showed no effect on adolescent PA. A mixed-methods process evaluation was embedded to facilitate greater understanding of the results, to elicit subgroup perceptions, and to provide insight into contextual factors influencing intervention implementation. This paper presents the reach, recruitment, dose, and fidelity of GoActive, and identifies challenges to implementation. The process evaluation employed questionnaires (1543 Year 9s), individual interviews (16 Year 9s; 7 facilitators; 9 contact teachers), focus groups (48 Year 9s; 58 mentors), alongside GoActive website analytics and researcher observations. GoActive sessions reached 39.4% of Year 9s. Intervention satisfaction was relatively high for mentors (87.3%) and facilitators (85.7%), but lower for Year 9s (59.5%) and teachers (50%). Intervention fidelity was mixed within and between schools. Mentorship was the most implemented component. Factors potentially contributing to low implementation included ambiguity of the roles subgroups played within intervention delivery, Year 9 engagement, institutional support, and further school-level constraints. Multiple challenges and varying contextual considerations hindered the implementation of GoActive in multiple school sites. Methods to overcome contextual challenges to implementation warrant in-depth consideration and innovative approaches.