Association between physical activity and self-regulation in early childhood: A systematic review.

Physical activity and self-regulation are important predictors of pediatric overweight and obesity. Young children (0-5 years) with lower physical activity levels and poorer self-regulation skills are at greater risk for overweight. Despite growing evidence that the two constructs are interrelated, their association remains unclear in young children. This review systematically summarized associations between physical activity and self-regulation in early childhood and explored the directionality of associations. Searches were run in six electronic databases. Forty-seven papers met inclusion criteria. Only three studies investigated all three domains of self-regulation (behavioral, cognitive, and emotional). Overall, findings were inconclusive; studies reported weak to moderate positive associations (n = 17), inverse associations (n = 5), mixed associations (n = 15), null association (n = 2), and negative (n = 1) between physical activity and self-regulation. Compared with the emotional and cognitive domains, physical activity was most consistently positively associated with behavioral self-regulation. Only one study assessed bidirectional associations, reporting a positive association. The three studies that included global self-regulation showed contradicting findings. There is some evidence that physical activity dose and sex potentially confound these associations; however, further research is needed given the paucity of studies. This review highlights the need for more in-depth investigation of the complex association between physical activity and global self-regulation.

Breastfeeding and the Longitudinal Changes of Body Mass Index in Childhood and Adulthood: A Systematic Review.

Mounting evidence supports the beneficial role of breastfeeding in lowering obesity risk, but the enduring impact of breastfeeding on longitudinal changes in body mass index (BMI) (i.e., BMI trajectories) remains unclear. This systematic review summarized evidence on how breastfeeding influenced the longitudinal trajectories of BMI later in life. Literature searches were conducted in Medline, Embase, Web of Science, and ScienceDirect to identify studies that assessed how breastfeeding (versus other feeding types or duration) was associated with longitudinal trajectories of BMI or BMI z-score. Three randomized controlled trials (RCTs) and 24 longitudinal cohort studies were included. Two-thirds (18/27) of studies were rated as acceptable or high quality. Most cohort studies (9/11) showed that children who continued to breastfeed at 3 to 12 mo of age had a lower BMI trajectory or lower odds of following a high BMI trajectory than those who were formula-fed or mixed-fed. The BMI differences between breastfeeding and other feeding groups were evident from age 7 mo and remained up to 8 y, and the magnitude of between-group BMI differences increased with age. For breastfeeding duration, 12 out of 15 cohort studies found that longer breastfeeding duration was associated with lower BMI trajectories up to age 18 y. Moreover, beneficial associations were observed for both exclusive and any breastfeeding with BMI trajectory. In contrast, mixed findings were reported from 3 RCTs that compared BMI trajectories from birth to ages 12 to 24 mo between breastfeeding promotion versus control or breastfeeding versus formula-feeding groups. The current review provides further longitudinal evidence from cohort studies that breastfeeding versus formula/mixed feeding or longer breastfeeding duration was associated with lower BMI trajectories. Such associations initiated in early childhood became more apparent with age and were sustained into early adulthood. The existing evidence substantiates the importance of breastfeeding promotion and continuation to support obesity prevention.

Cross-sectional and prospective associations between behavioural patterns and adiposity in school-aged children.

OBJECTIVE: Behavioural patterns are important in understanding the synergistic effect of multiple health behaviours on childhood adiposity. Most previous evidence assessing associations between patterns and adiposity were cross-sectional and investigated two or three behaviour domains within patterns. This study aimed to identify behavioural patterns comprising four behaviour domains and investigate associations with adiposity risk in children. DESIGN: Parent-report and accelerometry data were used to capture daily dietary, physical activity, sedentary behaviour and sleep data. Variables were standardised and included in the latent profile analysis to derive behavioural patterns. Trained researchers measured children's height, weight and waist circumference using standardised protocols. Associations of patterns and adiposity measures were tested using multiple linear regression. SETTING: Melbourne, Australia. PARTICIPANTS: A total of 337 children followed up at 6-8 years (T2) and 9-11 years (T3). RESULTS: Three patterns derived at 6-8 years were broadly identified to be healthy, unhealthy and mixed patterns. Patterns at 9-11 years were dissimilar except for the unhealthy pattern. Individual behaviours characterising the patterns varied over time. No significant cross-sectional or prospective associations were observed with adiposity at both time points; however, children displaying the unhealthy pattern had higher adiposity measures than other patterns. CONCLUSION: Three non-identical patterns were identified at 6-8 and 9-11 years. The individual behaviours that characterised patterns (dominant behaviours) at both ages are possible drivers of the patterns obtained and could explain the lack of associations with adiposity. Identifying individual behaviour pattern drivers and strategic intervention are key to maintain and prevent the decline of healthy patterns.

Differing associations with childhood outcomes using behavioural patterns derived from three data reduction techniques.

BACKGROUND: Behavioural patterns help to understand the influence of multiple health behaviours on childhood outcomes. Behavioural patterns derived using different data reduction techniques can be non-identical and may differentially associate with childhood outcomes. This study aimed to compare associations of behavioural patterns derived from three methods with three childhood outcomes. METHODS: Data were from the Healthy Active Preschool and Primary Years study when children were 6-8 years old (n = 432). Cluster analysis (CA), latent profile analysis (LPA) and principal component analysis (PCA) were used to derive behavioural patterns from children's diet, physical activity, sedentary behaviour and sleep data. Behavioural data were obtained through parent report and accelerometry. Children's height, weight and waist circumference were measured by trained study staff. Health-related quality of life data were obtained using the Pediatric Quality of Life Inventory and academic performance scores were from a national test. Associations between derived patterns from each method and each of the outcomes were tested using linear regression (adjusted for child age and sex and parent education). RESULTS: Three patterns were each derived using CA and LPA, and four patterns were derived using PCA. Each method identified a healthy, an unhealthy and a mixed (comprising healthy and unhealthy behaviours together) pattern. Differences in associations were observed between pattern groups from CA and LPA and pattern scores from PCA with the three outcomes. CONCLUSIONS: Discrepancies in associations across pattern derivation methods suggests that the choice of method can influence subsequent associations with outcomes. This has implications for comparison across studies that have employed different methods.

Longitudinal associations between weight status and academic achievement in primary school children.

BACKGROUND: Evidence for longitudinal associations between childhood weight status and academic achievement remains unclear due to considerable heterogeneity in study design, measures of academic achievement and appropriate categorization of weight status. OBJECTIVE: To examine longitudinal associations between childhood weight status (underweight, healthy weight, overweight/obese) and academic achievement in the transition from preschool to primary (elementary) school among Australian school children. METHODS: Data were from the Healthy Active Preschool and Primary Years study. Height and weight, for calculating BMI were measured at baseline (preschool age 3-5 years; 2008/9) and follow-up (primary school age 6-8 years; 2011/12). Academic achievement was measured at age 9 years. RESULTS: No associations between BMI z-score or weight category in the preschool years and later NAPLAN scores were found for boys. For girls, having a higher BMI z-score (B = -13.68, 95%CI: -26.61, -0.76) and being affected by overweight (B = -33.57, 95%CI: -61.50, -5.24) in preschool was associated with lower language scores. Remaining affected by overweight from preschool to primary school was associated with lower numeracy (B = -25.03, 95%CI: -49.74, -0.33), spelling (B = -33.5, 95%CI: -63.43, -3.58), language (B = -37.89, 95%CI: -72.75, -3.03) and total achievement scores (B = -24.24, 95%CI: -44.85, -3.63) among girls. For boys, becoming affected by overweight was associated with lower spelling (B = -38.76, 95%CI: -73.59, -3.93) and total achievement scores (B = -27.70, 95%CI: -54.81, -0.58). CONCLUSIONS: Associations between being affected by overweight/obesity and poorer academic achievement were more pronounced in girls than boys, indicating potentially inequitable impacts of excess weight and highlighting the greater need for intervention among girls. However, stronger study designs are needed to confirm our findings.

Associations between Child and Family Level Correlates and Behavioural Patterns in School-Aged Children.

Identifying correlates of behavioural patterns are important to target population sub-groups at increased health risk. The aim was to investigate correlates of behavioural patterns comprising four behavioural domains in children. Data were from the HAPPY study when children were 6-8 years (n = 335) and 9-11 years (n = 339). Parents reported correlate and behavioural data (dietary intake, physical activity, sedentary behaviour, and sleep). Behavioural data were additionally captured using accelerometers. Latent profile analysis was used to derive patterns. Patterns were identified as healthy, unhealthy, and mixed at both time points. Multinomial logistic regression tested for associations. Girls were more likely to display healthy patterns at 6-8 years and display unhealthy and mixed patterns at 9-11 years than boys, compared to other patterns at the corresponding ages. Increased risk of displaying the unhealthy pattern with higher age was observed at both timepoints. At 9-11 years, higher parental working hours were associated with lower risk of displaying mixed patterns compared to the healthy pattern. Associations observed revealed girls and older children to be at risk for unhealthy patterns, warranting customisation of health efforts to these groups. The number of behaviours included when deriving patterns and the individual behaviours that dominate each pattern appear to be drivers of the associations for child level, but not for family level, correlates.

A comparison of children's diet and movement behaviour patterns derived from three unsupervised multivariate methods.

BACKGROUND: Behavioural patterns are typically derived using unsupervised multivariate methods such as principal component analysis (PCA), latent profile analysis (LPA) and cluster analysis (CA). Comparability and congruence between the patterns derived from these methods has not been previously investigated, thus it's unclear whether patterns from studies using different methods are directly comparable. This study aimed to compare behavioural patterns derived across diet, physical activity, sedentary behaviour and sleep domains, using PCA, LPA and CA in a single dataset. METHODS: Parent-report and accelerometry data from the second wave (2011/12; child age 6-8y, n = 432) of the HAPPY cohort study (Melbourne, Australia) were used to derive behavioural patterns using PCA, LPA and CA. Standardized variables assessing diet (intake of fruit, vegetable, sweet, and savoury discretionary items), physical activity (moderate- to vigorous-intensity physical activity [MVPA] from accelerometry, organised sport duration and outdoor playtime from parent report), sedentary behaviour (sedentary time from accelerometry, screen time, videogames and quiet playtime from parent report) and sleep (daily sleep duration) were included in the analyses. For each method, commonly used criteria for pattern retention were applied. RESULTS: PCA produced four patterns whereas LPA and CA each generated three patterns. Despite the number and characterisation of the behavioural patterns derived being non-identical, each method identified a healthy, unhealthy and a mixed pattern. Three common underlying themes emerged across the methods for each type of pattern: (i) High fruit and vegetable intake and high outdoor play ("healthy"); (ii) poor diet (either low fruit and vegetable intake or high discretionary food intake) and high sedentary behaviour ("unhealthy"); and (iii) high MVPA, poor diet (as defined above) and low sedentary time ("mixed"). CONCLUSION: Within this sample, despite differences in the number of patterns derived by each method, a good degree of concordance across pattern characteristics was seen between the methods. Differences between patterns could be attributable to the underpinning statistical technique of each method. Therefore, acknowledging the differences between the methods and ensuring thorough documentation of the pattern derivation analyses is essential to inform comparison of patterns derived through a range of approaches across studies.

A systematic review of lifestyle patterns and their association with adiposity in children aged 5-12 years.

Diet, physical activity, sedentary behaviour and sleep are typically examined independently with childhood adiposity; however, their combined influence remains uncertain. This review aims to systematically summarize evidence on the clustering of these behaviours through lifestyle patterns and evaluate associations with adiposity in children aged 5-12 years. Search strategies were run in six databases. Twenty-eight papers met the inclusion criteria, six of which included all four behaviours. A range of lifestyle patterns were identified (healthy, unhealthy and mixed). Mixed patterns were most frequently reported. Unhealthy patterns comprising low physical activity and high sedentary behaviour were also frequently observed. Mixed patterns comprising healthy diets, low physical activity and high sedentary behaviour were more commonly seen in girls, whereas boys were more physically active, similarly sedentary and had unhealthier diets. Children from lower socio-economic backgrounds tended to more frequently display unhealthy patterns. Unhealthy lifestyle patterns were more often associated with adiposity risk than healthy and mixed patterns. With few studies including all four behaviours, it is difficult to establish a clear picture of their interplay and associations with adiposity. Nonetheless, reliance on lifestyle patterns is likely more beneficial than individual behaviours in targeting adiposity and improving understanding of how these behaviours influence health.