International Journal of Behavioral Nutrition and Physical Activity最新文献

Background: Foods are not purchased in isolation but are normally co-purchased with other food products. The patterns of co-purchasing associations across a large number of food products have been rarely explored to date. Knowledge of such co-purchasing patterns will help evaluate nutrition interventions that might affect the purchasing of multiple food items while providing insights about food marketing activities that target multiple food items simultaneously.

Objective: To quantify the association of food products purchased with each of three food categories of public health importance: soda, fresh fruits and fresh vegetables using Association Rule Mining (ARM) followed by longitudinal regression analysis.

Methods: We obtained transaction data containing grocery purchasing baskets (lists of purchased products) collected from loyalty club members in a major supermarket chain between 2015 and 2017 in Montréal, Canada. There were 72 food groups in these data. ARM was applied to identify food categories co-purchased with soda, fresh fruits, and fresh vegetables. A subset of co-purchasing associations identified by ARM was further tested by confirmatory logistic regression models controlling for potential confounders of the associations and correlated purchasing patterns within shoppers.

Results: We analyzed 1,692,716 baskets. Salty snacks showed the strongest co-purchasing association with soda (Relative Risk [RR] = 2.07, 95% Confidence Interval [CI]: 2.06, 2.09). Sweet snacks/candies (RR = 1.73, 95%CI: 1.72-1.74) and juices/drinks (RR:1.71, 95%CI:1.71-1.73) also showed strong co-purchasing associations with soda. Fresh vegetables and fruits showed considerably different patterns of co-purchasing associations from those of soda, with pre-made salad and stir fry showing a strong association (RR = 3.78, 95% CI:3.74-3.82 for fresh vegetables and RR = 2.79, 95%CI:2.76-2.81 for fresh fruits). The longitudinal regression analysis confirmed these associations after adjustment for the confounders, although the associations were weaker in magnitude.

Conclusions: Quantifying the interdependence of food products within shopping baskets provides novel insights for developing nutrition surveillance and interventions targeting multiple food categories while motivating research to identify drivers of such co-purchasing. ARM is a useful analytical approach to identify such cross-food associations from retail transaction data when combined with confirmatory regression analysis to adjust for confounders of such associations.

Background: This study aimed to explore socioecological correlates of parental lifestyle patterns during pregnancy, an overlooked topic except for individual socioeconomic factors.

Methods: We used data from three European mother-offspring cohorts participating in the EndObesity Consortium [EDEN, France, n = 1,962; Generation R, the Netherlands, n = 8,765; and Lifeways, Ireland, n = 932]. In previous principal component analysis, we identified two separate parental lifestyle patterns in pregnancy, characterised by: 1) "high parental smoking, poor-quality maternal diet, and low physical activity"; and 2) "low parental body mass index (BMI) and high gestational weight gain (GWG)". Applying the socioecological model, we conducted multivariable linear regression analyses on lifestyle pattern scores (outcomes), first including parental socioeconomic and sociodemographic characteristics (block 1), then the urban environment (block 2), and finally psychosocial factors and health-care access (block 3).

Results: Older parents, those born abroad, or with high SEP had lower scores for the first lifestyle pattern. Conversely, multiparous mothers, those with suboptimal health insurance coverage, or who did not attend parenting preparation sessions followed that pattern more closely. Multiparous mothers, parents with a low SEP, or living in highly deprived areas had lower scores on the second pattern, contrary to those exposed to high population density or living in a neighbourhood with high facility richness.

Conclusions: Higher SEP, a foreign birthplace, wealthier neighbourhoods, and attendance at antenatal parenting preparation sessions were associated with healthier parental lifestyles during pregnancy. These potential facilitators should be considered for inclusion in tailored family-based health promotion interventions during the perinatal period.

Background: Previous research has estimated the genetic and environmental contribution to individual differences in emotional overeating in toddlerhood and early childhood. However, little is known how this behaviour tracks into adolescence. Here, we aimed to replicated previous work and examine the aetiology of stability and change in emotional overeating across time.

Methods: Data were from the UK Gemini Twin Study, which includes 2402 twin pairs born in 2007. Parents reported on children's emotional overeating at 16 months (n = 3784), 5 years (n = 2064), and 12 years (n = 964), using the Emotional Overeating Scale of the Child Eating Behaviour Questionnaire (CEBQ) at 5 and 12 years, and the CEBQ-T (toddler version) at 16 months. A Cholesky Decomposition twin model was used to quantify the additive genetic, shared, and nonshared environmental influences on emotional overeating at each time point, partitioned into aetiological effects unique to each age and those carried across time.

Results: Additive genetic effects were minimal at 16 months and 5 years (9% and 7% respectively) but increased to 34% by 12 years. Shared environmental effects explained the majority of variance in emotional overeating at all three time points, but significantly less at 12 years (41%) than earlier (> 81%). The longitudinal phenotypic associations (r = 0.23-0.43) were explained by the shared environment.

Conclusion: The shared environment plays a major role in the development of emotional overeating in early life. Most aetiological influences on emotional overeating were unique to each age, indicating the need for family-based interventions targeted to each developmental stage.

Background: Children with avid eating behaviour display high food responsiveness, high emotional overeating and low sensitivity to fullness; behaviours which may increase the risk of obesity and are challenging for parents to manage. This study explores the situational predictors of coercive or indulgent feeding practices among parents of children with avid eating behaviours using Ecological Momentary Assessment (EMA).

Methods: The study involved 109 parents of 3-5-year-old children exhibiting avid eating behaviour. Over 10 days, participants completed EMA surveys via a mobile app to report on their mood, stress, feeding goals, and feeding practices during eating occasions. Multilevel modelling was used to assess how parental mood, goals, and the eating context (e.g., meal versus snack, public versus private setting) influenced feeding practices.

Results: Parents were more likely to use specific coercive or indulgent feeding practices when experiencing higher stress, when aiming to avoid mealtime conflict, and during meals versus snacks. A negative meal atmosphere and a public setting also increased the likelihood of certain indulgent practices. Notably, parents were more likely to report giving their child food to calm them down or help manage their behaviour when the meal atmosphere was perceived as negative and if they aimed to reduce conflict at the meal. The findings highlight that the context of feeding occasions significantly drives the use of coercive or indulgent feeding practices.

Conclusions: Parental stress, goals, and the eating context are key determinants of coercive or indulgent feeding practices with children exhibiting avid eating behaviours. Interventions to support parents should consider these dynamic factors, promoting healthier feeding strategies tailored to real-life contexts.

Background: Few studies have empirically examined the impact of school salad bars on elementary students' fruit and vegetable (FV) consumption within the National School Lunch Program (NSLP). This natural experiment evaluated the impact of salad bars on FV selection, intake, and waste within elementary schools.

Methods: Seven school pairs, matched on Title I status and percentage of students from ethnic or racial minority backgrounds, were randomly selected. All schools served pre-portioned FV at baseline. One school within each pair received a salad bar; the other continued to serve pre-portioned FV (Control). Digital imagery plate waste methods were applied at baseline and 4-6 weeks after schools installed salad bars (post). Images were rated in the laboratory (ICCs = .94-.99) to determine FV selection, intake, and waste (servings [1 NSLP serving = ½c]). Multilevel modeling evaluated group (Salad Bar vs Control) and time (baseline vs post) differences and group-by-time interactions. Differences in outcomes by Title I status were also examined.

Results: Across schools, mean NSLP participation was 54%. N = 6,623 trays were included (n = 3,273 Salad Bar; n = 3,350 Control). Students in Salad Bar schools selected (+ .44c) and consumed (+ .36c) more FV at post, compared to baseline. Control students decreased FV selection (-.05c) with no change in intake from baseline to post. Group, time, and group-by-time interactions were significant (ps < .0001). When examined separately, results suggest that these effects are driven by fruit. Salad Bar students increased fruit selection (+ .45c), intake (+ .36c), and waste (+ .09c) from baseline to post; no significant changes were observed in Controls. There was no significant change in vegetable selection, intake or waste for either group. Findings did not differ based on Title I status.

Conclusions: Salad bars were effective in increasing elementary school students' fruit selection and intake, yet did not increase vegetable selection or intake. Additional efforts are needed to increase vegetable intake and minimize fruit waste from salad bars. Consistent findings across schools, regardless of Title I status, suggest potential for salad bars to yield increased fruit intake across socioeconomic groups. Findings can inform policies designed to increase FV intake within the NSLP.

Trial registration: This investigation reports results of a systematic evaluation of school salad bars and does not meet criteria for a clinical trial, yet was retrospectively registered (10/28/22) in clinicaltrials.gov (NCT05605483) as an observational study.

Background: Early childhood obesity prevention interventions that aim to change parent/caregiver practices related to infant (milk) feeding, food provision and parent feeding, movement (including activity, sedentary behaviour) and/or sleep health (i.e. target parental behaviour domains) are diverse and heterogeneously reported. We aimed to 1) systematically characterise the target behaviours, delivery features, and Behaviour Change Techniques (BCTs) used in interventions in the international Transforming Obesity Prevention for CHILDren (TOPCHILD) Collaboration, and 2) explore similarities and differences in BCTs used in interventions by target behaviour domains.

Methods: Annual systematic searches were performed in MEDLINE, Embase, Cochrane (CENTRAL), CINAHL, PsycINFO, and two clinical trial registries, from inception to February 2023. Trialists from eligible randomised controlled trials of parent-focused, behavioural early obesity prevention interventions shared unpublished intervention materials. Standardised approaches were used to code target behaviours, delivery features and BCTs in both published and unpublished intervention materials. Validation meetings confirmed coding with trialists. Narrative syntheses were performed.

Results: Thirty-two trials reporting 37 active intervention arms were included. Interventions targeted a range of behaviours. The most frequent combination was targeting all parental behaviour domains (infant [milk] feeding, food provision and parent feeding, movement, sleep health; n[intervention arms] = 15/37). Delivery features varied considerably. Most interventions were delivered by a health professional (n = 26/36), included facilitator training (n = 31/36), and were interactive (n = 28/36). Overall, 49 of 93 unique BCTs were coded to at least one target behaviour domain. The most frequently coded BCTs were: Instruction on how to perform a behaviour (n[intervention arms, separated by domain] = 102), Behavioural practice and rehearsal (n = 85), Information about health consequences (n = 85), Social support (unspecified) (n = 84), and Credible source (n = 77). Similar BCTs were often used for each target behaviour domain.

Conclusions: Our study provides the most comprehensive description of the behaviour change content of complex interventions targeting early childhood obesity prevention available to date. Our analysis revealed that interventions targeted multiple behaviour domains, with significant variation in delivery features. Despite the diverse range of BCTs coded, five BCTs were consistently identified across domains, though certain BCTs were more prevalent in specific domains. These findings can be used to examine effectiveness of components and inform intervention development and evaluation in future trials.

Trial registration: PROSPERO registration no. CRD42020177408.

Background: The workplace is an important determinant of health that people are exposed to for the first-time during adolescence or early adulthood. This study investigates how diet, physical activity, and sleep change as people aged 16-30 years transition into work and whether this varies for different individuals and job types.

Methods: Multilevel linear regression models assessed changes in fruit and vegetable intake, sleep duration, and physical activity among 3,302 UK Household Longitudinal Study (UKHLS) participants aged 16-30 years, who started work for the first time between 2015 and 2023. In line with interrupted time series analysis, models assessed behavioural trends in the period before starting work, the immediate effect of starting work, and changes in behaviour over time after employment. Stratified analyses examined differences by selected individual and job characteristics, adjusted for covariates. All analyses were conducted in R v.4.3.2.

Results: Sleep duration was stable over the years before and after starting work, but starting work was associated with an immediate reduction in sleep duration (β[Formula: see text]-9.74 [95% CI:-17.32 to -2.17 min/night). Physical activity, measured in Metabolic Equivalent Tasks (METs), increased immediately after starting work (β = 113.3, [95% CI: 80.49 to 146.11] MET-min/day), but subsequently decreased over time after starting work (β= -26.7, [95% CI: -40.75 to -12.66] MET-min/day/year). The increase in physical activity was greater among males, among those with no degree and among those starting lower socioeconomic classification jobs. Starting a "work from home" job had an immediate negative effect on physical activity (β= -126.42 [95% CI: -264.45 to 11.61] MET-min/day), whereas those who worked at their employer's premises showed an initial increase (β = 128.81 [95% CI: 89.46 to 168.16] MET-min/day). Starting work had little influence on fruit and vegetable consumption.

Conclusions: This is the first study to examine how diet, physical activity, and sleep in young adults change as they start employment in the UK. Starting work is associated with decreased sleep time and increased physical activity, with differences based on sociodemographic and job characteristics. Future research should consider these potential influences of the work environment when developing interventions to promote healthy behaviour in the workplace.

Background: Depression and anxiety may significantly affect women in the menopausal transition and menopause. In addition to traditional treatment strategies such as hormone therapy, antidepressants, and psychotherapy, physical activity (PA) have been increasingly studied, but there is no consensus about their role in menopausal women with depression and anxiety.

Objective: The current study aimed to evaluate the effect of PA on the severity of depressive (DS) and anxiety (AS) symptoms in women during the menopausal transition and menopause.

Methods: We searched for relevant published studies in PubMed, Embase, Web of Science, Cochrane Library, and CINAHL prior to 8 April 2024, focusing on randomized controlled trials documenting the effect of physical activity on DS and AS, and assessed study quality using the Newcastle-Ottawa Scale.

Results: The data used for meta-analysis were derived from 21 studies (DS, n = 9; AS, n = 1; DS and AS combined, n = 11) involving 2020 participants. The results showed that PA groups demonstrated a statistically significant effect of depressive symptoms versus controls (DS [SMD: -0.66, 95% CI: -0.99 to -0.33; P < 0.001]; AS [SMD: -0.55, 95% CI: -0.82 to -0.27; P < 0.001]). As subgroup analyses demonstrated, physical exercise also reduced depressive symptom of women in menopausal status (SMD =-0.56, 95% CI: -0.96 to - 0.17, p = 0.006, I² = 69%), postmenopausal status (SMD =-0.94, 95% CI: -1.46 to - 0.42, p = 0.0004, I² = 94%), and both in menopausal transition and postmenopausal status (SMD =-0.30, 95% CI: -0.49 to - 0.12, p = 0.001, I² = 0%), while it only reduced anxiety symptom of postmenopausal women (SMD =-0.96, 95% CI: -1.49 to - 0.43, p = 0.0004, I² = 89%). Low-intensity and moderate-intensity exercise both produced increasingly benefits over depressive and anxiety symptoms. However, there is no statistically significant effect of exercise intensity on both depressive symptom and anxiety symptom.

Conclusion: Physical activities with low to moderate intensity can impart remarkable improvements for managing menopausal women with depression and anxiety.

Background: Movement behaviors, including physical activity (PA), sedentary behavior (SB), and sleep, are fundamental to early childhood development. These behaviors interact dynamically within a 24-hour period, creating a complex balance that influences not only physical health but also cognitive and emotional well-being in young children. While the physical health benefits of movement behaviors are well-documented, systematic evaluations of how interventions targeting these behaviors affect cognitive development in preschool-aged children remain limited.

Methods: This review was guided through PRISMA 2020 guidelines. We conducted a systematic review of randomized controlled trials (RCTs) to evaluate the impact of interventions targeting PA, SB, and sleep on cognitive outcomes in preschool-aged children. A comprehensive search was performed across five databases: PubMed, PsycInfo, Web of Science, Embase, and CINAHL, covering studies published between January 2000 and December 2023. Eligible studies were those that focused on at least one movement behavior, had a minimum intervention duration of four weeks, and assessed cognitive development as a primary outcome. The cognitive outcomes evaluated included executive function, attention, memory, and other key domains critical to early childhood development, such as language, processing speed, and social cognition.

Results: Twenty-two RCTs (14 individual, 8 cluster) met the inclusion criteria. Of these, 21 studies focused on PA, while only one targeted SB, and none specifically addressed sleep or combined movement behaviors. PA interventions, particularly those involving cognitively engaging activities, significantly improved cognitive domains such as executive function, inhibition, and attention, with effect sizes ranging from moderate to large (Cohen's d > 0.5). The SB-focused study did not report significant cognitive improvements. A clear gap exists in understanding the effects of sleep and multi-behavior interventions on cognitive outcomes.

Conclusions: Cognitively engaging PA interventions demonstrated the largest effects, while motor skill-focused and general PA programs produced moderate to smaller gains. Evidence on SB and sleep interventions remains limited, with no studies exploring the combined effects of these three movement behaviors. Future research should focus on integrated interventions that address PA, SB, and sleep to achieve a more comprehensive understanding of their collective impact on cognitive development in early childhood.

Trial registration: This study was registered with PROSPERO under the registration number CRD42023479156.

Background: This study aims to investigate the associations between signal-level physical activity (PA) features derived from wrist accelerometry data and cognitive status in older adults, and to evaluate their potential predictive value when combined with demographics.

Methods: We analyzed PA data from 3,363 older adults (NHATS: n = 747; NHANES: n = 2,616), with each participant contributing a complete 3-day continuous activity sequence. We extracted the most relevant PA features associated with cognitive function using feature engineering and recursive feature elimination. Demographic characteristics were also incorporated, and multimodal data fusion was achieved through canonical correlation analysis. We then developed explainable machine learning models, primarily random forest, optimized with hyperparameters, to predict individual cognitive function status.

Results: Using recursive feature elimination, we identified the top 20 PA features from each dataset and combined them with demographic features for modeling. The models achieved AUCs of 0.84 and 0.80 for NHATS and NHANES. Change quantiles and FFT coefficients emerged as the consistently top-ranked PA features across datasets, ranking 1st and 2nd respectively in their predictive importance for cognitive function. Models based on the top 10 PA features common to both datasets, along with demographic features, achieved AUCs above 0.8.

Conclusions: This study identifies novel time-frequency domain features of physical activity that show robust associations with cognitive status across two independent cohorts. These features, particularly those capturing activity variability and rhythmicity, provide complementary information beyond traditional cumulative PA measures. Based on these findings, we developed a proof-of-concept application that demonstrates the feasibility of translating these PA analytics into practical monitoring tools in real-world settings.