International Journal of Behavioral Nutrition and Physical Activity最新文献

Background: Unfavourable changes occur in children's health behaviours and outcomes during the summer holidays. This systematic review aimed to determine the effectiveness of summer holiday programs in mitigating these changes.

Methods: Six databases (MEDLINE, JBI, PsychINFO, Embase, ERIC and Scopus) were systematically searched for experimental controlled studies that investigated programs of at least 5 days' duration conducted exclusively during the summer holiday period on school-aged children (5-18 years). Primary outcomes were moderate-vigorous physical activity and energy intake. Secondary outcomes were sedentary behavior, diet quality, adiposity, and cardiorespiratory fitness. Risk of Bias was assessed using the PEDro tool. Effect sizes were calculated using random-effects meta-analysis with narrative synthesis of effects by student or program characteristics.

Results: Ten studies (two randomised controlled trials, and eight non-randomised controlled trials) involving 1,446 participants were included. Summer programs had a significant moderate effect on reducing sedentary behaviour (g= -0.59, 95%CI= -1.16, -0.03) and significant small effects on improving moderate-to-vigorous physical activity (g = 0.35, 95%CI = 0.02, 0.67) and adiposity (g= -0.25, 95% CI = -0.39, -0.10). No significant change was detected for cardiorespiratory fitness (g = 0.43, 95%CI= -0.32, 1.17), energy intake (g= -0.06, 95% CI -2.33, 2.22), or diet quality (g = 0.20, 95%CI= -0.43, 0.83). Summer program effectiveness did not appear to differ by child sociodemographic or program characteristics. Concerns regarding bias and high heterogeneity impacted results.

Conclusions: Summer programs show potential in promoting healthier movement behaviours in children and supporting healthy body weight during the summer months. Although evidence from the included studies has limitations, these programs produced small to moderate effect sizes and present promising health intervention opportunities for children. Future research with more rigorous study designs and comprehensive reporting is needed to confirm these findings and better understand the impact of summer programs on children's health.

Prospero registration: CRD42023409795.

Background: Physical activity and sleep are established modifiable lifestyle factors, but the optimal time of the day of these behaviours for health is unknown. This study examined the independent and joint associations of diurnal patterns of physical activity and sleep with all-cause mortality.

Methods: This prospective cohort study included 6,673 participants who have attended the accelerometer assessment in the 2011-2014 National Health and Nutrition Examination Surveys (NHANES). Diurnal patterns of accelerometer-measured physical activity and sleep were identified using K-means clustering analysis. All-cause mortality was ascertained from the accelerometer measurement to December 31, 2019 (median follow-up 6.8 years). Survey-weighted Cox proportional hazard models were performed to estimate the independent and joint associations of diurnal patterns of physical activity and sleep with all-cause mortality.

Results: Diurnal patterns identified were: early-morning (32.4%), midday (42.5%), and late-afternoon (25.1%) for physical activity; and irregular sleep (37.4%), morning lark (33.6%), and night owl (29.0%) for sleep. After adjusting for volume of physical activity, sleep duration and other potential covariates, the early-morning physical activity pattern (hazard ratio 1.36, 95% confidence interval 1.13-1.64) and irregular sleep pattern (1.42, 1.01-1.99) were independently associated with higher risk of all-cause mortality, compared with midday physical activity and morning lark sleep patterns, respectively. In addition, participants with the combined pattern of early-morning physical activity and irregular sleep had higher risk of all-cause mortality compared to those with midday physical activity combined with a morning lark sleep pattern (1.92, 1.33-2.78). Several sociodemographic differences were observed in the strength of these associations.

Conclusions: Wearable activity-rest monitoring data showed that peak physical activity in the early morning and irregular sleep diurnal patterns are associated with increased mortality risk, and the combination of these patterns further exaggerated the risk. Public health program should acknowledge that the diurnal patterns of physical activity and sleep, in addition to their duration and frequency, may play a crucial role in lifestyle-based health promotion and management strategies.

Background: While complementary feeding can be challenging, little emphasis has been placed on the introduction to food texture/pieces, especially in terms of neurodevelopmental outcomes. This study aims to determine the association between the timing of introduction to food pieces during infancy and neurodevelopment in early childhood. We hypothesized that late introduction to food texture/pieces relates to unfavorable neurodevelopmental outcomes.

Methods: Families (n = 18329) were recruited from the general population during the nationwide ELFE (Étude Longitudinale Française depuis l'Enfance) birth cohort in France, and 8511 were selected for a complete case analysis. Age at introduction to food pieces was determined based on repeated assessments during the first year. A range of neurodevelopmental outcomes among children were assessed using validated instruments, i.e. composite scores at 1 and 3.5 years, and a score for language acquisition at 2 years. Risk for developmental delay at 3.5 years was defined based on a developmental quotient (DQ) below 90 according to the child's chronological age and the respective composite score at this age. We used linear regression modelling to evaluate associations between age at introduction to food pieces and the standardised neurodevelopmental scores, while logistic regression models were used in the analyses according to the risk for developmental delay.

Results: Our findings highlight consistent associations between late introduction to food pieces (i.e., after 10 months, compared to early (before 8 months)) and lower estimates of standardised neurodevelopmental scores at ages 1, 2 and 3.5 years (-0.35 [-0.40; -0.30], -0.15 [-0.20; -0.10] and - 0.18 [-0.23; -0.13], respectively). Infants introduced to pieces late were also more likely to be at risk for developmental delay according to DQ < 90 (OR [95%CI] = 1.62 [1.36; 1.94]).

Conclusions: This study shows that late introduction to food pieces (> 10 months) is related to lower neurodevelopmental scores. Given the challenges that complementary feeding may pose, concerted efforts are required to enhance our understanding of the sensory aspects of early diets and to ultimately provide guidance.

Background: The benefits of healthy eating are well known, yet adolescent diet is often poor. School based interventions offer a promising option to promote healthy eating, however, evidence is unclear.

Aim: This umbrella review synthesised the current evidence on school-based interventions for healthy eating in adolescents (10-19 years old).

Methods: Using Joanna Briggs Institute (JBI) umbrella review guidelines, a systematic search was conducted on 11 electronic databases (PubMed, CINHAL, EMBASE, Science Direct, PsycINFO, MEDLINE, Scopus, ERIC, Web of Science, Cochrane Register of Systemic Review and JBI Evidence Synthesis) to identify reviews published between January 2000 and December 2023. Methodological quality was assessed using JBI critical appraisal tool. A narrative synthesis was conducted informed by the World Health Organisation's Health Promoting School (HPS) framework that categorises school-based interventions into three components i.e., health education, school environment changes, and family and community involvement.

Results: Seventeen reviews were identified (including 347 unique primary studies) that were published between 2008 and 2023. 87% of the reviews were based on interventions in high- income countries, limiting applicability to low- and middle-income countries. Fourteen reviews were rated as high, two as moderate, and one was rated as low methodological quality. Evidence from 71% of the reviews (n = 14 reviews, 13 = high methodological quality) found that multi-component interventions (i.e., interventions incorporating more than two components of the HPS framework) improved adolescents' knowledge and behaviour concerning healthy eating. At the individual level, tech-driven healthy eating curricula effectively improved eating behaviours of adolescents. These individual-level interventions proved to be more effective and sustainable when supported by system-level changes, such as modifying school environments including increased availability of healthy foods and involving parents to promote healthy eating for adolescents. However, limited evidence from only three reviews suggests mixed feasibility for technology-based interventions and lower feasibility for multi-component interventions. The lack of information on stakeholder involvement in intervention design is another critical evidence gap.

Conclusion: School-based multi-component healthy eating interventions that combine individual-level interventions with system-level changes are effective in promoting healthy eating behaviours among adolescents. Future reviews should assess the effectiveness of participatory approaches in intervention design, feasibility and scale-up studies, and analysing evidence from low- and middle-income countries.

Background: Nutrient content and degree of processing are complementary but distinct concepts, and a growing body of evidence shows that ultra-processed foods (UPFs) can have detrimental health effects independently from nutrient content. 10 + countries currently mandate front-of-package labels (FOPL) to inform consumers when products are high in added sugars, saturated fat, and/or sodium. Public health advocates have been calling for the addition of ultra-processed warning labels to these FOPLs, but the extent to which consumers would understand and be influenced by such labels remains unknown. We examined whether the addition of ultra-processed warning labels to existing nutrient warning labels could influence consumers' product perceptions and purchase intentions.

Methods: In 2023, a sample of adults in Brazil (n = 1,004) answered an open-ended question about the meaning of the term "ultra-processed," followed by an online experiment where they saw four ultra-processed products carrying warning labels. Participants were randomly assigned to view either only nutrient warning labels or nutrient plus ultra-processed warning labels. Participants then answered questions about their intentions to purchase the products, product perceptions, and perceived label effectiveness.

Results: Most participants (69%) exhibited a moderate understanding of the term "ultra-processed" prior to the experiment. The addition of an ultra-processed warning label led to a higher share of participants who correctly identified the products as UPFs compared to nutrient warning labels alone (Cohen's d = 0.16, p = 0.02). However, the addition of the ultra-processed warning label did not significantly influence purchase intentions, product healthfulness perceptions, or perceived label effectiveness compared to nutrient warning labels alone (all p > 0.05). In exploratory analyses, demographic characteristics and prior understanding of the concept of UPF did not moderate the effect of ultra-processed warning labels.

Conclusions: Ultra-processed warning labels may help consumers better identify UPFs, although they do not seem to influence behavioral intentions and product perceptions beyond the influence already exerted by nutrient warning labels. Future research should examine how ultra-processed warning labels would work for products that do and do not require nutrient warnings, as well as examine the benefits of labeling approaches that signal the health effects of UPFs.

Trial registration: ClinicalTrials.gov, NCT05842460. Prospectively registered March 15th, 2023.

Background: Sleep, sedentary behaviour, and physical activity are essential components within the 24-hour time frame. Existing questionnaires used to measure these behaviours have insufficient measurement properties and are unsuitable for assessing compliance with the WHO Physical Activity and 24-hour Movement Guidelines. To describe the development process of the 24-hour Movement Questionnaire (QMov24h) and its testing. The QMov24h was developed to gather detailed information on sleep, sedentary behaviour, and physical activity.

Methods: The sample comprised 117 participants (58% women), aged 30.95 ± 13.56 years. The development process of the QMov24h followed the COSMIN guidelines: (i) Construction of items; (ii) Face validity with end-users; (iii) Content validity with experts; (iv) Criterion validity against accelerometry and convergent validity against diary assessments; and (v) 7-day test-retest reliability.

Results: The QMov24h presented adequate content and face validity. The QMov24h showed moderate criterion validity for sleep (rho=0.343;p<0.001), light physical activity (rho=0.31;p=0.002) and total aerobic physical activity (rho=0.343;p<0.001), as well as strong criterion validity for sedentary behaviour (rho=0.428;p<0.001) and aerobic moderate-to-vigorous physical activity (rho=0.534;p<0.001). Reliability varied from poor to excellent (ICC from 0.38 to 0.962;p<0.001) for all questionnaire variables. Regarding compliance of the 24-hour movement guidelines, the questionnaire also showed a strong to almost perfect percentage of agreement with accelerometry (from 69% to 94.3%), and minimal to strong reliability (k from 0.38 to 0.87) between the first and second administrations of the QMov24h.

Conclusions: The QMov24h questionnaire is a valid and reliable tool for assessing levels of movement behaviours and compliance with guidelines in adults. Its measurement properties are comparable to, or even better than, those of existing questionnaires, while posing a similar burden to participants. The QMov24h is useful for research, clinical practice, and public health surveillance. The QMov24h has strong psychometric properties, making it suitable for translation, cultural adaptation, and testing in diverse populations for broader international use.

Background: Secondary schools are important settings for promoting varied physical activity (PA) opportunities for adolescents to promote PA throughout life. However, research on the effect of secondary school-based interventions on future PA is limited. This study examined the potential impact of secondary school-based interventions on the determinants of future PA participation of Aotearoa New Zealand (NZ) adolescents using simulated modelling.

Methods: We used data from a nationally representative sample of secondary school students (n = 5035) aged 12-17 between 2017 and 2020 in NZ. We modelled four secondary school-based interventions and their projected impact on five determinants of future PA. Modelled interventions were the technological augmentation of physical education (TAPE), a peer-led PA mentoring programme (PL), physically active learning (PAL) and the inclusion of a natural environment play area (NE).

Results: Total weekly PA increased the most from the NE intervention (+ 0.2 h/week), followed by TAPE (+ 0.08 h/week), PAL (+ 0.05 h/week) and PL (-0.06 h/week). Current number of PA settings increased the most in NE (+ 1.75 settings/week), followed by TAPE (+ 1.29 settings/week), PAL (+ 1.21 settings/week) and PL (+ 0.73 settings/week). Current number of PA types increased the most in NE (+ 1.57 types/week), followed by PL (+ 1.05 types/week), TAPE (+ 0.34 types/week) and PAL (+ 0.15 types/week). Physical literacy scores increased the most from PL (+ 3.6%), followed by PAL (+ 3.3%), TAPE (+ 0.43%) and NE (+ 0.12%). Social support scores increased the most from PAL (+ 5%), followed by PL (+ 1.9%), TAPE (+ 1.46%) and NE (+ 0.57%).

Conclusions: On average, all interventions benefitted determinants of future PA participation to a small degree. Results show differing magnitudes of the intervention effect by determinant, indicating the complexities surrounding the promotion of PA adherence. Future interventions could be improved through detailed consultation alongside, and involving, adolescents and stakeholders within schools. Researchers should also prioritise the collection of longitudinal PA data and explore its connection with sociodemographic differences between adolescents.

Background: The online BeUpstanding™ program is an eight-week workplace-delivered intervention for desk-based workers to raise awareness of the benefits of sitting less and moving more and build a supportive culture for change. A workplace representative (the "champion") delivers the program, which includes a workshop where teams collectively choose their sit less/move more strategies. A toolkit provides the champion with a step-by-step guide and associated resources to support program uptake, delivery, and evaluation. Here we report on the main findings from the Australian national implementation trial of BeUpstanding.

Methods: Recruitment (12/06/2019 to 30/09/2021) was supported by five policy and practice partners, with desk-based work teams from across Australia targeted. Effectiveness was measured via a single arm, repeated-measures trial. Data were collected via online surveys, toolkit analytics, and telephone calls with champions. The RE-AIM framework guided evaluation, with adoption/reach (number and characteristics); effectiveness (primary: self-reported workplace sitting time); implementation (completion of core components; costs); and, maintenance intentions reported here. Linear mixed models, correcting for cluster, were used for effectiveness, with reach, adoption, implementation, and maintenance outcomes described.

Results: Of the 1640 website users who signed-up to BeUpstanding during the recruitment period, 233 were eligible, 198 (85%) provided preliminary consent, and 118 (50.6%) champions consented and started the trial, with 94% (n = 111 champions) completing. Trial participation was from across Australia and across industries, and reached 2,761 staff, with 2,248 participating in the staff survey(s): 65% female; 64% university educated; 17% from a non-English speaking background. The program effectively changed workplace sitting (-38.5 [95%CI -46.0 to -28.7] minutes/8-hour workday) and all outcomes targeted by BeUpstanding (behaviours and culture), with small-to-moderate statistically-significant effects observed. All participating teams (n = 94) completed at least 5/7 core steps; 72.4% completed all seven. Most champions spent $0 (72%) or >$0-$5 (10%) per team member; most (67/70 96%) intended to continue or repeat the program.

Conclusions: BeUpstanding can be adopted and successfully implemented by a range of workplaces, reach a diversity of staff, and be effective at creating a supportive culture for teams of desk-based workers to sit less and move more. Learnings will inform optimisation of the program for longer-term sustainability.

Trial registration: ACTRN12617000682347.

Background: Studies have shown that prolonged television watching increases obesity risk among children. However, few studies examined the associations with other types of screen time, such as computer and smartphone use, using a prospective cohort study design. Further, little is known about the specific non-screen time activity that may yield the most benefits when reallocating screen time to other activities.

Methods: We conducted a prospective cohort analysis using 3-year follow-up data from the Korean Children and Youth Panel Survey 2018 (n = 2,023; 4th grade elementary students who were not obese at baseline). Average time spent watching television, using computer and smartphone, and other after-school activities were self-reported at baseline. Weight and height were also self-reported at baseline and follow-up surveys through 2021. We performed multivariable logistic regression models to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for the associations between screen time and obesity incidence, adjusting for potential confounders. We also performed isotemporal substitution models to examine the associations of reallocating screen time to other non-screen time activities (physical activity, sleeping, hanging out with friends, reading, studying, and chatting with parents) in an equal time-exchange manner.

Results: Longer combined screen time (≥ 240 vs. <120 m/d) was statistically significantly associated with an increased obesity risk (OR [95% CI] = 1.68 [1.03, 2.73]). The direction of associations with television watching (≥ 180 vs. <60 m/d: OR [95% CI] = 2.86 [1.58, 5.20]), computer use (≥ 120 vs. <60 m/d: 1.38 [0.52, 3.64]), and smartphone use (≥ 180 vs. <60 m/d: 1.42 [0.76, 2.65]) were all positive, although the association was most apparent and statistically significant for television watching only. The associations did not change after additional adjustment for other lifestyle factors, including physical activity, sleep, and breakfast skipping. In the isotemporal substitution models, reallocating 1-hour of screen time to reading (OR [95% CI] = 0.67 [0.48, 0.93]) was associated with a decreased obesity risk. Reallocating 1-hour of screen time to physical activity was only marginally significantly associated with obesity risk (0.79 [0.62, 1.01]).

Conclusions: Our data suggest that more efforts should focus on reducing screen time and increasing time for other non-screen time activities, particularly reading, for obesity prevention in children.