International Journal of Behavioral Nutrition and Physical Activity最新文献

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.

Background: Non-communicable diseases are rising rapidly in low- and middle-income countries, leading to increased morbidity and mortality. Reducing sedentary behavior (SB) and increasing physical activity (PA) offer numerous health benefits. Workplaces provide an ideal setting for promoting SB/PA interventions; however, understanding the barriers and enablers is crucial for optimizing these interventions in workplace environments.

Methods: Nested within a cluster randomised controlled trial (the SMART-STEP trial), the present study employed in-depth interviews with 16 office workers who have completed 24 weeks of two distinct (technology assisted and traditional) workplace SB/PA interventions. Using a deductive analysis, semi-structured interviews were administered to explore the barriers and enablers to the SB/PA interventions at individual, interpersonal and organisational level using the socio-ecological model.

Results: Several individual (poor goal setting, perceived health benefits & workload, attitude, intervention engagement), interpersonal (lack of peer support) and organisational (task prioritisation, lack of organisational norm and material or social reward) barriers were identified. Indian women engaged in desk-based office jobs often find themselves burdened with intense home and childcare responsibilities, often without sufficient support from their spouses. A primary concern among Indian office workers is the poor awareness and absence of cultural norms regarding the health risks associated with SB.

Conclusions: Raising awareness among workplace stakeholders-including office workers, peers, and the organization-is crucial before designing and implementing SB/PA interventions in Indian workspaces. Personalized interventions for Indian female office workers engaged in desk-bound work are warranted.

Background: Identifying lifestyle factors that independently or jointly lower dementia risk is a public health priority given the limited treatment options available to patients. In this cohort study, we examined the associations between Mediterranean or Dietary Approaches to Stop Hypertension (DASH) diet adherence and cardiorespiratory fitness (CRF) with later-life dementia, and assessed whether the associations between dietary pattern and dementia are modified by CRF.

Methods: Data are from 9,095 adults seeking preventive care at the Cooper Clinic (1987-1999) who completed a 3-day dietary record and a maximal exercise test. Alzheimer's disease and related disorders or senile dementia (i.e., all-cause dementia) was identified from Medicare administrative claims (1999-2019). Illness-death models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the associations between Mediterranean or DASH diet adherence (primary exposure), CRF (secondary exposure), and all-cause dementia, adjusted for demographic and clinical factors. An interaction term was included between diet score and CRF to assess effect modification by CRF.

Results: The mean age at baseline was 50.6 (standard deviation [SD]: 8.4) years, and a majority of the study sample were men (77.5%) and White (96.4%). 1449 cases of all-cause dementia were identified over a mean follow-up of 9.2 (SD: 5.8) years. Neither Mediterranean nor DASH diet adherence was associated with dementia risk in fully adjusted models (HR per SD of Mediterranean diet score: 1.00, 95% CI: 0.94, 1.05; HR per SD of DASH diet score: 1.02, 95% CI: 0.96, 1.08). However, participants with higher CRF had a decreased hazard of dementia (HR, per metabolic equivalent of task [MET] increase, Mediterranean model: 0.95, 95% CI: 0.92, 0.98; HR, per MET increase, DASH model: 0.96, 95% CI: 0.92, 0.97). No effect modification by CRF was observed in the association between diet and dementia.

Conclusions: In this sample of apparently healthy middle-aged adults seeking preventive care, higher CRF at midlife was associated with a lower risk of all-cause dementia, though adherence to a Mediterranean or DASH diet was not, and CRF did not modify the diet-dementia association. CRF should be emphasized in multimodal interventions for dementia prevention and investigated among diverse samples.

Background: The PROMIS^® Early Childhood Physical Activity (PROMIS EC PA) scale is a recently developed PROMIS Early Childhood measure to assess PA among children aged 1-5 years. The purpose of this study was to examine test-retest reliability and convergent validity of the PROMIS EC PA scale among toddlers.

Method: An ancillary study was conducted in the toddler-mother dyad sample of the Child and Mother Physical Activity Study. Mothers completed the 7-item PROMIS EC PA scale twice: during a study visit (test) and on the last day when their child's wore an ActiGraph accelerometer on the hip for 7 days (retest). The PROMIS EC PA summed score was calculated by totaling scores from items 1-5. Test-retest reliability was assessed using intraclass correlation coefficient (ICC) for test and retest PROMIS EC PA. Convergent validity was assessed using rank correlation coefficients (rho) between PROMIS EC PA scores and accelerometer-measured moderate- and vigorous-intensity PA (MVPA).

Results: Among 74 participants (56% female; 19 ± 4 months of mean age with range of 12-30 months), average accelerometer-measured MVPA was 76 ± 24 min/day. The median number of days between PROMIS EC PA test and retest was 8 days (IQR = 6 to 8), with an average PROMIS EC PA summed score of 11.0 ± 3.5 at test and 10.5 ± 3.4 at retest. ICC for the test-retest PROMIS EC PA summed scores was 0.72 (95% CI = 0.59-0.82). The rank correlation between the PROMIS EC PA summed score and accelerometer-measured MVPA was 0.13 (95% CI=-0.10 to 0.35; p = 0.28).

Conclusion: In a sample of children aged 12-30 months, test-retest reliability for the PROMIS EC PA scale was moderate and its convergent validity against accelerometer-measured MVPA was poor. Prior to a widespread use of the PROMIS EC PA scale in large-scale research and clinical practice, the tool should be further refined and validated to elucidate how young children's lived PA experience as measured in the PROMIS EC PA scale is relevant to their health and wellbeing outcomes.

Background: Randomized controlled trials have confirmed the effectiveness of four prevalent caloric restriction regimens in reducing obesity-related health risks. However, there is no consensus on the optimal regimen for weight management in adults.

Methods: We systematically searched PubMed, Embase, Web of Science, and Cochrane CENTRAL up to January 15, 2024, for randomized controlled trials (RCT) involving adults, evaluating the weight-loss effects of alternate day fasting (ADF), short-term fasting (STF), time-restricted eating (TRE), and continuous energy restriction (CER). The primary outcome was body weight, with secondary outcomes including BMI, fat mass, lean mass, waist circumference, fasting glucose, HOMA-IR, and adverse events. Bayesian network meta-analysis was conducted, ranking regimens using the surface under the cumulative ranking curve and the probability of being the best. Study quality was assessed using the Confidence in Network Meta-Analysis tool.

Results: Data from 47 RCTs (representing 3363 participants) were included. ADF showed the most significant body weight loss (Mean difference (MD): -3.42; 95% Confidence interval (CI): -4.28 to -2.55), followed by TRE (MD: -2.25; 95% CI: -2.92 to -1.59). STF (MD: -1.87; 95% CI: -3.32 to -0.56) and CER (MD: -1.59; 95% CI: -2.42 to -0.79) rank third and fourth, respectively. STF lead to decline in lean mass (MD: -1.26; 95% CI: -2.16, -0.47). TRE showed benefits on fasting glucose (MD: -2.98; 95% CI: -4.7, -1.26). Subgroup analysis revealed all four caloric restriction regimens likely lead to modest weight loss after 1-3 months, with ADF ranked highest, but by 4-6 months, varying degrees of weight regain occur, particularly with CER, while interventions lasting 7-12 months may result in effective weight loss, with TRE potentially ranking first during both the 4-6 months and 7-12 months periods. ADF showing fewer and shorter-lasting physical symptoms.

Conclusion: All four included regiments were effective in reducing body weight, with ADF likely having the most significant impact. Each regimen likely leads to modest weight loss after 1-3 months, followed by weight regain by 4-6 months. However, interventions lasting 7-12 months achieve greater weight loss overall.

Trial registration: PROSPERO: CRD42022382478.

Background: Despite the observed associations of personality traits with levels of moderate-to-vigorous physical activity (MVPA) and sedentary behavior (SB), studies exploring whether the personality profiles differ in terms of the pattern of accumulation of physical behavior are lacking. The aim of this study was to identify adults' personality profiles and to characterize and investigate how these profiles differ in physical behavior.

Methods: The study utilized the longitudinal data of the participants of the Jyväskylä Longitudinal Study of Personality and Social Development (n = 141-307). Information on the five-factor model of personality, including the traits of neuroticism, extraversion, conscientiousness, openness, and agreeableness, was collected at ages 33, 42, 50, and 61 years, and used to create latent personality profiles. Physical behavior, operationalized as the amount and accumulation of MVPA and SB bouts, was captured using a triaxial accelerometer worn during waking hours at age 61 years. The differences in the behavior between the personality profiles were analyzed using the Kruskal-Wallis test.

Results: Five personality profiles were identified: resilient (20.2%), brittle (14.0%), overcontrolled (9.8%), undercontrolled (15.3%), and ordinary (40.7%). Although there were no statistically significant differences between the personality profiles in the time spent in MVPA relative to SB (MVPA per hour of daily SB), individuals with resilient (low in neuroticism and high in other traits) and ordinary (average in each trait) profiles had MVPA-to-SB ratios of 0.12 (7 min) and those with a brittle (high in neuroticism and low in extraversion) profile had a ratio of 0.09 (5.5 min). The individuals in the resilient group exhibited a longer usual MVPA bout duration than those in the overcontrolled (low in extraversion, openness, and agreeableness) (8 min vs. 2 min) and undercontrolled (high in openness and low in conscientiousness) groups (8 min vs. 3 min). They also exhibited a longer usual SB bout duration than those in the ordinary group (29 min vs. 23 min).

Conclusions: The resilient group displayed the most prolonged MVPA and SB bout patterns. The results suggest that personality characteristics may contribute to how MVPA and SB are accumulated.