Prospective associations of lifestyle patterns in early childhood with socio-emotional and behavioural development and BMI: An outcome-wide analysis of the EDEN mother-child cohort

Clusters of 24-hour movement behavior and diet and their relationship with health indicators among youth: a systematic review

Movement-related behaviors (physical activity [PA], sedentary behavior [SB], and sleep) and diet interact with each other and play important roles in health indicators in youth. This systematic review aimed to investigate how PA, SB, sleep, and diet cluster in youth by biological sex; and to examine which cluster are associated with health indicators. This study was registered in PROSPERO (number: CRD42018094826). Five electronic databases were assessed. Eligibility criteria allowed studies that included youth (aged 19 years and younger), and only the four behaviors {PA, SB, sleep, and diet (ultra-processed foods [UPF]; fruits and vegetables [FV])} analyzed by applying data-based cluster procedures. From 12,719 articles screened; 23 were included. Of these, four investigated children, and ten identified clusters by biological sex. Sixty-six mixed cluster were identified including, 34 in mixed-sex samples, 10 in boys and 11 in girls. The most frequent clusters in mixed-sex samples were "High SB UPF Low Sleep", "Low PA High SB Satisfactory Sleep", and "High PA". The main difference in profiles according to sex was that girls' clusters were characterized by high sleep duration, whereas boys' clusters by high PA. There were a few associations found between cluster types and health indicators, highlighting that youth assigned to cluster types with low PA exhibited higher adiposity. In conclusion, the youth presented a range of clusters of behaviors, typically exhibiting at least one unhealthy behavior. Similar patterns were observed in both sexes with the biggest difference in time of sleep for girls and PA for boys. These findings underscore the importance of intervention strategies targeting multiple behaviors simultaneously to enhance health risk profiles and indicators in children and adolescents.

Beyond the single-outcome approach: A comparison of outcome-wide analysis methods for exposome research

Outcome-wide analysis can offer several benefits, including increased power to detect weak signals and the ability to identify exposures with multiple effects on health, which may be good targets for preventive measures. Recently, advanced statistical multivariate techniques for outcome-wide analysis have been developed, but they have been rarely applied to exposome analysis. In this work, we provide an overview of a selection of methods that are well-suited for outcome-wide exposome analysis and are implemented in the R statistical software. Our work brings together six different methods presenting innovative solutions for typical problems arising from outcome-wide approaches in the context of the exposome, including dependencies among outcomes, high dimensionality, mixed-type outcomes, missing data records, and confounding effects. The identified methods can be grouped into four main categories: regularized multivariate regression techniques, multi-task learning approaches, dimensionality reduction approaches, and bayesian extensions of the multivariate regression framework. Here, we compare each technique presenting its main rationale, strengths, and limitations, and provide codes and guidelines for their application to exposome data. Additionally, we apply all selected methods to a real exposome dataset from the Human Early-Life Exposome (HELIX) project, demonstrating their suitability for exposome research. Although the choice of the best method will always depend on the challenges to be faced in each application, for an exposome-like analysis we find dimensionality reduction and bayesian methods such as reduced rank regression (RRR) or multivariate bayesian shrinkage priors (MBSP) particularly useful, given their ability to deal with critical issues such as collinearity, high-dimensionality, missing data or quantification of uncertainty.

[Association Between Medication Compliance and Various Risky Behaviors in Patients With Schizophrenia]

Objective

To investigate the status of medication adherence and various types of risky behaviors of schizophrenia patients in a certain area of western China and to explore accordingly the correlation between the two.

Methods

A total of 292 667 patients with schizophrenia were enrolled in a follow-up survey between 2006 and 2018. In addition, based on the outcome-wide analysis strategy, a multivariate Cox proportional risk regression model was used to estimate and compare the impact of medication adherence on different types of risky behaviors in schizophrenia patients.

Results

In this 13-year prospective cohort, 65 175 patients (31.4%) showed good medication adherence, while 142 394 patients (68.6%) showed poor medication adherence. The incidence rates of various risky behaviors during the follow-up period were as follows, minor nuisances, 12.25%, violation of the Law of the People's Republic of China on Penalties for Administration of Public Security (APS law), 3.82%, violation of criminal law, 0.94%, suicide completed, 0.28%, self-harm, 1.42%, and attempted suicide, 0.82%. Schizophrenia patients who had poor medication adherence had higher risks of committing violence against others and self-inflicted injury compared to patients with good medication adherence did, with the associated effects being minor nuisances (hazard ratio [HR]=1.31, 95% confidence interval [CI]: 1.27-1.35), violation of APS law (HR=1.47, 95% CI: 1.38-1.56), violation of criminal law (HR=1.17, 95% CI: 1.05-1.31), and self-harm (HR=1.43, 95% CI: 1.32-1.56), respectively, while the risk of suicide completed is lower in schizophrenia patients with poor medication adherence than that in patients with good medication adherence (HR=0.56, 95% CI: 0.47-0.66). There was no statistically significant association between attempted suicide and medication adherence.

Conclusion

There are variations in the direction and strength of the association between medication adherence and different types of risky behaviors and further research is needed to elucidate the mechanisms of the association.

Lifestyle Patterns of Children Experiencing Homelessness: Family Socio-Ecological Correlates and Links with Physical and Mental Health

Diet, screen time, physical activity, and sleep combine into lifestyle patterns with synergistic effects on health. This study aimed to identify lifestyle patterns in children without housing and assess their associations with physical and mental health and family socio-ecological factors. In the 2013 ENFAMS cross-sectional survey (children aged 6-12 experiencing homelessness, Greater Paris area, n = 235), parents reported socio-ecological factors, children's behaviours, and mental health (the latter was also child-reported). Nurses measured children's haemoglobin concentrations and body mass index. Principal component analysis was used to derive sex-specific lifestyle patterns. Hierarchical linear regressions and "outcome-wide" analyses assessed, respectively, these patterns' relations to health and family socio-ecological factors. A rather healthy lifestyle pattern-similarly characterized by diverse diet and high sleep time-was identified, with slight differences by sex. Scores for this pattern were higher for children in food-secure or higher-income households, whose parents were proficient in French, who slept longer, or who received more social support compared to their counterparts, with some nuances by sex. Higher scores for this pattern were associated with higher prosocial behaviour scores (girls) and lower anxiety and hyperactivity-inattention symptoms scores (boys), but not with physical health. For this underserved and understudied population, the results highlight the importance of family socio-ecological factors in shaping the lifestyles and mental health of children.