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Background Antenatal depression can have harmful consequences for the mother and fetus. Exercise may be a useful intervention to prevent and treat antenatal depression.Objectives This systematic review aims to establish whether there is sufficient evidence to conclude that exercise is an effective intervention for preventing and treating antenatal depression.Search strategy Searches using electronic databases from MEDLINE, Cochrane Library, CINAHL, EMBASE, AMED and PsycINFO were performed.Selection criteria Randomised controlled trials (RCT) that compared any type of exercise intervention with any comparator in pregnant women were eligible for inclusion.Data collection and analysis Meta-analysis was performed calculating standardised mean differences (SMD).Main results Six trials (seven comparisons) were eligible for inclusion. Meta-analysis showed a significant reduction in depression scores (SMD À0.46, 95% CI À0.87 to À0.05, P = 0.03, I 2 = 68%) for exercise interventions relative to comparator groups.The test for subgroup differences in women who were non-depressed (one trial) (SMD À0.74, 95%CI À1.22 to À0.27, P = 0.002) and depressed (five trials) (SMD À0.41, 95% CI À0.88 to 0.07, P = 0.09) at baseline was not significant (P = 0.32). The test for subgroup differences between aerobic (one trial) and non-aerobic exercise (five trials) was also nonsignificant (P = 0.32).Authors' conclusions We found some evidence that exercise may be effective in treating depression during pregnancy but this conclusion is based on a small number of low-moderate quality trials with significant heterogeneity and wide confidence intervals.

AimTo examine individual variability between perceived physical features and hormones of pubertal maturation in 9–10-year-old children as a function of sociodemographic characteristics.MethodsCross-sectional metrics of puberty were utilized from the baseline assessment of the Adolescent Brain Cognitive Development (ABCD) Study—a multi-site sample of 9–10 year-olds (n = 11,875)—and included perceived physical features via the pubertal development scale (PDS) and child salivary hormone levels (dehydroepiandrosterone and testosterone in all, and estradiol in females). Multi-level models examined the relationships among sociodemographic measures, physical features, and hormone levels. A group factor analysis (GFA) was implemented to extract latent variables of pubertal maturation that integrated both measures of perceived physical features and hormone levels.ResultsPDS summary scores indicated more males (70%) than females (31%) were prepubertal. Perceived physical features and hormone levels were significantly associated with child’s weight status and income, such that more mature scores were observed among children that were overweight/obese or from households with low-income. Results from the GFA identified two latent factors that described individual differences in pubertal maturation among both females and males, with factor 1 driven by higher hormone levels, and factor 2 driven by perceived physical maturation. The correspondence between latent factor 1 scores (hormones) and latent factor 2 scores (perceived physical maturation) revealed synchronous and asynchronous relationships between hormones and concomitant physical features in this large young adolescent sample.ConclusionsSociodemographic measures were associated with both objective hormone and self-report physical measures of pubertal maturation in a large, diverse sample of 9–10 year-olds. The latent variables of pubertal maturation described a complex interplay between perceived physical changes and hormone levels that hallmark sexual maturation, which future studies can examine in relation to trajectories of brain maturation, risk/resilience to substance use, and other mental health outcomes.

During late childhood behavioral changes, such as increased risk-taking and emotional reactivity, have been associated with the maturation of cortico-cortico and cortico-subcortical circuits. Understanding microstructural changes in both white matter and subcortical regions may aid our understanding of how individual differences in these behaviors emerge. Restriction spectrum imaging (RSI) is a framework for modelling diffusion-weighted imaging that decomposes the diffusion signal from a voxel into hindered, restricted, and free compartments. This yields greater specificity than conventional methods of characterizing diffusion. Using RSI, we quantified voxelwise restricted diffusion across the brain and measured age associations in a large sample (n = 8086) from the Adolescent Brain and Cognitive Development (ABCD) study aged 9–14 years. Older participants showed a higher restricted signal fraction across the brain, with the largest associations in subcortical regions, particularly the basal ganglia and ventral diencephalon. Importantly, age associations varied with respect to the cytoarchitecture within white matter fiber tracts and subcortical structures, for example age associations differed across thalamic nuclei. This suggests that age-related changes may map onto specific cell populations or circuits and highlights the utility of voxelwise compared to ROI-wise analyses. Future analyses will aim to understand the relevance of this microstructural developmental for behavioral outcomes.

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