Social inequalities in pregnancy metabolic profile: findings from the multi-ethnic Born in Bradford cohort study.

BACKGROUND: Lower socioeconomic position (SEP) associates with adverse pregnancy and perinatal outcomes and with less favourable metabolic profile in nonpregnant adults. Socioeconomic differences in pregnancy metabolic profile are unknown. We investigated association between a composite measure of SEP and pregnancy metabolic profile in White European (WE) and South Asian (SA) women. METHODS: We included 3,905 WE and 4,404 SA pregnant women from a population-based UK cohort. Latent class analysis was applied to nineteen individual, household, and area-based SEP indicators (collected by questionnaires or linkage to residential address) to derive a composite SEP latent variable. Targeted nuclear magnetic resonance spectroscopy was used to determine 148 metabolic traits from mid-pregnancy serum samples. Associations between SEP and metabolic traits were examined using linear regressions adjusted for gestational age and weighted by latent class probabilities. RESULTS: Five SEP sub-groups were identified and labelled 'Highest SEP' (48% WE and 52% SA), 'High-Medium SEP' (77% and 23%), 'Medium SEP' (56% and 44%) 'Low-Medium SEP' (21% and 79%), and 'Lowest SEP' (52% and 48%). Lower SEP was associated with more adverse levels of 113 metabolic traits, including lower high-density lipoprotein (HDL) and higher triglycerides and very low-density lipoprotein (VLDL) traits. For example, mean standardized difference (95%CI) in concentration of small VLDL particles (vs. Highest SEP) was 0.12 standard deviation (SD) units (0.05 to 0.20) for 'Medium SEP' and 0.25SD (0.18 to 0.32) for 'Lowest SEP'. There was statistical evidence of ethnic differences in associations of SEP with 31 traits, primarily characterised by stronger associations in WE women e.g., mean difference in HDL cholesterol in WE and SA women respectively (vs. Highest-SEP) was -0.30SD (-0.41 to -0.20) and -0.16SD (-0.27 to -0.05) for 'Medium SEP', and -0.62SD (-0.72 to -0.52) and -0.29SD (-0.40 to -0.20) for 'Lowest SEP'. CONCLUSIONS: We found widespread socioeconomic differences in metabolic traits in pregnant WE and SA women residing in the UK. Further research is needed to understand whether the socioeconomic differences we observe here reflect pre-conception differences or differences in the metabolic pregnancy response. If replicated, it would be important to explore if these differences contribute to socioeconomic differences in pregnancy outcomes.

Sleep duration in preschool age and later behavioral and cognitive outcomes: an individual participant data meta-analysis in five European cohorts.

Short sleep duration has been linked to adverse behavioral and cognitive outcomes in schoolchildren, but few studies examined this relation in preschoolers. We aimed to investigate the association between parent-reported sleep duration at 3.5 years and behavioral and cognitive outcomes at 5 years in European children. We used harmonized data from five cohorts of the European Union Child Cohort Network: ALSPAC, SWS (UK); EDEN, ELFE (France); INMA (Spain). Associations were estimated through DataSHIELD using adjusted generalized linear regression models fitted separately for each cohort and pooled with random-effects meta-analysis. Behavior was measured with the Strengths and Difficulties Questionnaire. Language and non-verbal intelligence were assessed by the Wechsler Preschool and Primary Scale of Intelligence or the McCarthy Scales of Children's Abilities. Behavioral and cognitive analyses included 11,920 and 2981 children, respectively (34.0%/13.4% of the original sample). In meta-analysis, longer mean sleep duration per day at 3.5 years was associated with lower mean internalizing and externalizing behavior percentile scores at 5 years (adjusted mean difference: - 1.27, 95% CI [- 2.22, - 0.32] / - 2.39, 95% CI [- 3.04, - 1.75]). Sleep duration and language or non-verbal intelligence showed trends of inverse associations, however, with imprecise estimates (adjusted mean difference: - 0.28, 95% CI [- 0.83, 0.27] / - 0.42, 95% CI [- 0.99, 0.15]). This individual participant data meta-analysis suggests that longer sleep duration in preschool age may be important for children's later behavior and highlight the need for larger samples for robust analyses of cognitive outcomes. Findings could be influenced by confounding or reverse causality and require replication.

Long-term cardiometabolic health in people born after assisted reproductive technology: a multi-cohort analysis.

AIMS: To examine associations of assisted reproductive technology (ART) conception (vs. natural conception: NC) with offspring cardiometabolic health outcomes and whether these differ with age. METHODS AND RESULTS: Differences in systolic (SBP) and diastolic blood pressure (DBP), heart rate (HR), lipids, and hyperglycaemic/insulin resistance markers were examined using multiple linear regression models in 14 population-based birth cohorts in Europe, Australia, and Singapore, and results were combined using meta-analysis. Change in cardiometabolic outcomes from 2 to 26 years was examined using trajectory modelling of four cohorts with repeated measures. 35 938 (654 ART) offspring were included in the meta-analysis. Mean age ranged from 13 months to 27.4 years but was <10 years in 11/14 cohorts. Meta-analysis found no statistical difference (ART minus NC) in SBP (-0.53 mmHg; 95% CI:-1.59 to 0.53), DBP (-0.24 mmHg; -0.83 to 0.35), or HR (0.02 beat/min; -0.91 to 0.94). Total cholesterol (2.59%; 0.10-5.07), HDL cholesterol (4.16%; 2.52-5.81), LDL cholesterol (4.95%; 0.47-9.43) were statistically significantly higher in ART-conceived vs. NC offspring. No statistical difference was seen for triglycerides (TG), glucose, insulin, and glycated haemoglobin. Long-term follow-up of 17 244 (244 ART) births identified statistically significant associations between ART and lower predicted SBP/DBP in childhood, and subtle trajectories to higher SBP and TG in young adulthood; however, most differences were not statistically significant. CONCLUSION: These findings of small and statistically non-significant differences in offspring cardiometabolic outcomes should reassure people receiving ART. Longer-term follow-up is warranted to investigate changes over adulthood in the risks of hypertension, dyslipidaemia, and preclinical and clinical cardiovascular disease.

Gestational age at birth and body size from infancy through adolescence: An individual participant data meta-analysis on 253,810 singletons in 16 birth cohort studies.

BACKGROUND: Preterm birth is the leading cause of perinatal morbidity and mortality and is associated with adverse developmental and long-term health outcomes, including several cardiometabolic risk factors and outcomes. However, evidence about the association of preterm birth with later body size derives mainly from studies using birth weight as a proxy of prematurity rather than an actual length of gestation. We investigated the association of gestational age (GA) at birth with body size from infancy through adolescence. METHODS AND FINDINGS: We conducted a two-stage individual participant data (IPD) meta-analysis using data from 253,810 mother-child dyads from 16 general population-based cohort studies in Europe (Denmark, Finland, France, Italy, Norway, Portugal, Spain, the Netherlands, United Kingdom), North America (Canada), and Australasia (Australia) to estimate the association of GA with body mass index (BMI) and overweight (including obesity) adjusted for the following maternal characteristics as potential confounders: education, height, prepregnancy BMI, ethnic background, parity, smoking during pregnancy, age at child's birth, gestational diabetes and hypertension, and preeclampsia. Pregnancy and birth cohort studies from the LifeCycle and the EUCAN-Connect projects were invited and were eligible for inclusion if they had information on GA and minimum one measurement of BMI between infancy and adolescence. Using a federated analytical tool (DataSHIELD), we fitted linear and logistic regression models in each cohort separately with a complete-case approach and combined the regression estimates and standard errors through random-effects study-level meta-analysis providing an overall effect estimate at early infancy (>0.0 to 0.5 years), late infancy (>0.5 to 2.0 years), early childhood (>2.0 to 5.0 years), mid-childhood (>5.0 to 9.0 years), late childhood (>9.0 to 14.0 years), and adolescence (>14.0 to 19.0 years). GA was positively associated with BMI in the first decade of life, with the greatest increase in mean BMI z-score during early infancy (0.02, 95% confidence interval (CI): 0.00; 0.05, p < 0.05) per week of increase in GA, while in adolescence, preterm individuals reached similar levels of BMI (0.00, 95% CI: -0.01; 0.01, p 0.9) as term counterparts. The association between GA and overweight revealed a similar pattern of association with an increase in odds ratio (OR) of overweight from late infancy through mid-childhood (OR 1.01 to 1.02) per week increase in GA. By adolescence, however, GA was slightly negatively associated with the risk of overweight (OR 0.98 [95% CI: 0.97; 1.00], p 0.1) per week of increase in GA. Although based on only four cohorts (n = 32,089) that reached the age of adolescence, data suggest that individuals born very preterm may be at increased odds of overweight (OR 1.46 [95% CI: 1.03; 2.08], p < 0.05) compared with term counterparts. Findings were consistent across cohorts and sensitivity analyses despite considerable heterogeneity in cohort characteristics. However, residual confounding may be a limitation in this study, while findings may be less generalisable to settings in low- and middle-income countries. CONCLUSIONS: This study based on data from infancy through adolescence from 16 cohort studies found that GA may be important for body size in infancy, but the strength of association attenuates consistently with age. By adolescence, preterm individuals have on average a similar mean BMI to peers born at term.

Correction: Gestational age at birth and body size from infancy through adolescence: An individual participant data meta-analysis on 253,810 singletons in 16 birth cohort studies.

[This corrects the article DOI: 10.1371/journal.pmed.1004036.].

Associations of Maternal Educational Level, Proximity to Greenspace During Pregnancy, and Gestational Diabetes With Body Mass Index From Infancy to Early Adulthood: A Proof-of-Concept Federated Analysis in 18 Birth Cohorts.

International sharing of cohort data for research is important and challenging. We explored the feasibility of multi-cohort federated analyses by examining associations between three pregnancy exposures (maternal education, exposure to green vegetation and gestational diabetes) with offspring BMI from infancy to 17 years. We used data from 18 cohorts (n=206,180 mother-child pairs) from the EU Child Cohort Network and derived BMI at ages 0-1, 2-3, 4-7, 8-13 and 14-17 years. Associations were estimated using linear regression via one-stage IPD meta-analysis using DataSHIELD. Associations between lower maternal education and higher child BMI emerged from age 4 and increased with age (difference in BMI z-score comparing low with high education age 2-3 years = 0.03 [95% CI 0.00, 0.05], 4-7 years = 0.16 [95% CI 0.14, 0.17], 8-13 years = 0.24 [95% CI 0.22, 0.26]). Gestational diabetes was positively associated with BMI from 8 years (BMI z-score difference = 0.18 [CI 0.12, 0.25]) but not at younger ages; however associations attenuated towards the null when restricted to cohorts which measured GDM via universal screening. Exposure to green vegetation was weakly associated with higher BMI up to age one but not at older ages. Opportunities of cross-cohort federated analyses are discussed.

Effect of common pregnancy and perinatal complications on offspring metabolic traits across the life course: a multi-cohort study.

BACKGROUND: Common pregnancy and perinatal complications are associated with offspring cardiometabolic risk factors. These complications may influence multiple metabolic traits in the offspring and these associations might differ with offspring age. METHODS: We used data from eight population-based cohort studies to examine and compare associations of pre-eclampsia (PE), gestational hypertension (GH), gestational diabetes (GD), preterm birth (PTB), small (SGA) and large (LGA) for gestational age (vs. appropriate size for gestational age (AGA)) with up to 167 plasma/serum-based nuclear magnetic resonance-derived metabolic traits encompassing lipids, lipoproteins, fatty acids, amino acids, ketones, glycerides/phospholipids, glycolysis, fluid balance, and inflammation. Confounder-adjusted regression models were used to examine associations (adjusted for maternal education, parity age at pregnancy, ethnicity, pre/early pregnancy body mass index and smoking, and offspring sex and age at metabolic trait assessment), and results were combined using meta-analysis by five age categories representing different periods of the offspring life course: neonates (cord blood), infancy (mean ages: 1.1-1.6 years), childhood (4.2-7.5 years); adolescence (12.0-16.0 years), and adulthood (22.0-67.8 years). RESULTS: Offspring numbers for each age category/analysis varied from 8925 adults (441 PTB) to 1181 infants (135 GD); 48.4% to 60.0% were females. Pregnancy complications (PE, GH, GD) were each associated with up to three metabolic traits in neonates (P≤0.001) with some evidence of persistence to older ages. PTB and SGA were associated with 32 and 12 metabolic traits in neonates respectively, which included an adjusted standardised mean difference of -0.89 standard deviation (SD) units for albumin with PTB (95% CI: -1.10 to -0.69, P=1.3×10-17) and -0.41 SD for total lipids in medium HDL with SGA (95% CI: -0.56 to -0.25, P=2.6×10-7), with some evidence of persistence to older ages. LGA was inversely associated with 19 metabolic traits including lower levels of cholesterol, lipoproteins, fatty acids, and amino acids, with associations emerging in adolescence, (e.g. -0.11 SD total fatty acids, 95% CI: -0.18 to -0.05, P=0.0009), and attenuating with older age across adulthood. CONCLUSIONS: These reassuring findings suggest little evidence of wide-spread and long-term impact of common pregnancy and perinatal complications on offspring metabolic traits, with most associations only observed for newborns rather than older ages, and for perinatal rather than pregnancy complications.

Measures of Early-life Behavior and Later Psychopathology in the LifeCycle Project - EU Child Cohort Network: A Cohort Description.

BACKGROUND: The EU LifeCycle Project was launched in 2017 to combine, harmonize, and analyze data from more than 250,000 participants across Europe and Australia, involving cohorts participating in the EU-funded LifeCycle Project. The purpose of this cohort description is to provide a detailed overview of the major measures within mental health domains that are available in 17 European and Australian cohorts participating in the LifeCycle Project. METHODS: Data on cognitive, behavioral, and psychological development has been collected on participants from birth until adulthood through questionnaire and medical data. We developed an inventory of the available data by mapping individual instruments, domain types, and age groups, providing the basis for statistical harmonization across mental health measures. RESULTS: The mental health data in LifeCycle contain longitudinal and cross-sectional data from birth throughout the life course, covering domains across a wide range of behavioral and psychopathology indicators and outcomes, including executive function, depression, ADHD, and cognition. These data span a unique combination of qualitative data collected through behavioral/cognitive/mental health questionnaires and examination, as well as data from biological samples and indices in the form of imaging (MRI, fetal ultrasound) and DNA methylation data. Harmonized variables on a subset of mental health domains have been developed, providing statistical equivalence of measures required for longitudinal meta-analyses across instruments and cohorts. CONCLUSION: Mental health data harmonized through the LifeCycle project can be used to study life-course trajectories and exposure-outcome models that examine early life risk factors for mental illness and develop predictive markers for later-life disease.

Associations of early-life pet ownership with asthma and allergic sensitization: A meta-analysis of more than 77,000 children from the EU Child Cohort Network.

BACKGROUND: Studies examining associations of early-life cat and dog ownership with childhood asthma have reported inconsistent results. Several factors could explain these inconsistencies, including type of pet, timing, and degree of exposure. OBJECTIVE: Our aim was to study associations of early-life cat and dog ownership with asthma in school-aged children, including the role of type (cat vs dog), timing (never, prenatal, or early childhood), and degree of ownership (number of pets owned), and the role of allergic sensitization. METHODS: We used harmonized data from 77,434 mother-child dyads from 9 birth cohorts in the European Union Child Cohort Network when the child was 5 to 11 years old. Associations were examined through the DataSHIELD platform by using adjusted logistic regression models, which were fitted separately for each cohort and combined by using random effects meta-analysis. RESULTS: The prevalence of early-life cat and dog ownership ranged from 12% to 45% and 7% to 47%, respectively, and the prevalence of asthma ranged from 2% to 20%. There was no overall association between either cat or dog ownership and asthma (odds ratio [OR] = 0.97 [95% CI = 0.87-1.09] and 0.92 [95% CI = 0.85-1.01], respectively). Timing and degree of ownership did not strongly influence associations. Cat and dog ownership were also not associated with cat- and dog-specific allergic sensitization (OR = 0.92 [95% CI = 0.75-1.13] and 0.93 [95% CI = 0.57-1.54], respectively). However, cat- and dog-specific allergic sensitization was strongly associated with school-age asthma (OR = 6.69 [95% CI = 4.91-9.10] and 5.98 [95% CI = 3.14-11.36], respectively). There was also some indication of an interaction between ownership and sensitization, suggesting that ownership may exacerbate the risks associated with pet-specific sensitization but offer some protection against asthma in the absence of sensitization. CONCLUSION: Our findings do not support early-life cat and dog ownership in themselves increasing the risk of school-age asthma, but they do suggest that ownership may potentially exacerbate the risks associated with cat- and dog-specific allergic sensitization.

Using linear and natural cubic splines, SITAR, and latent trajectory models to characterise nonlinear longitudinal growth trajectories in cohort studies.

BACKGROUND: Longitudinal data analysis can improve our understanding of the influences on health trajectories across the life-course. There are a variety of statistical models which can be used, and their fitting and interpretation can be complex, particularly where there is a nonlinear trajectory. Our aim was to provide an accessible guide along with applied examples to using four sophisticated modelling procedures for describing nonlinear growth trajectories. METHODS: This expository paper provides an illustrative guide to summarising nonlinear growth trajectories for repeatedly measured continuous outcomes using (i) linear spline and (ii) natural cubic spline linear mixed-effects (LME) models, (iii) Super Imposition by Translation and Rotation (SITAR) nonlinear mixed effects models, and (iv) latent trajectory models. The underlying model for each approach, their similarities and differences, and their advantages and disadvantages are described. Their application and correct interpretation of their results is illustrated by analysing repeated bone mass measures to characterise bone growth patterns and their sex differences in three cohort studies from the UK, USA, and Canada comprising 8500 individuals and 37,000 measurements from ages 5-40 years. Recommendations for choosing a modelling approach are provided along with a discussion and signposting on further modelling extensions for analysing trajectory exposures and outcomes, and multiple cohorts. RESULTS: Linear and natural cubic spline LME models and SITAR provided similar summary of the mean bone growth trajectory and growth velocity, and the sex differences in growth patterns. Growth velocity (in grams/year) peaked during adolescence, and peaked earlier in females than males e.g., mean age at peak bone mineral content accrual from multicohort SITAR models was 12.2 years in females and 13.9 years in males. Latent trajectory models (with trajectory shapes estimated using a natural cubic spline) identified up to four subgroups of individuals with distinct trajectories throughout adolescence. CONCLUSIONS: LME models with linear and natural cubic splines, SITAR, and latent trajectory models are useful for describing nonlinear growth trajectories, and these methods can be adapted for other complex traits. Choice of method depends on the research aims, complexity of the trajectory, and available data. Scripts and synthetic datasets are provided for readers to replicate trajectory modelling and visualisation using the R statistical computing software.

The EU Child Cohort Network's core data: establishing a set of findable, accessible, interoperable and re-usable (FAIR) variables.

The Horizon2020 LifeCycle Project is a cross-cohort collaboration which brings together data from multiple birth cohorts from across Europe and Australia to facilitate studies on the influence of early-life exposures on later health outcomes. A major product of this collaboration has been the establishment of a FAIR (findable, accessible, interoperable and reusable) data resource known as the EU Child Cohort Network. Here we focus on the EU Child Cohort Network's core variables. These are a set of basic variables, derivable by the majority of participating cohorts and frequently used as covariates or exposures in lifecourse research. First, we describe the process by which the list of core variables was established. Second, we explain the protocol according to which these variables were harmonised in order to make them interoperable. Third, we describe the catalogue developed to ensure that the network's data are findable and reusable. Finally, we describe the core data, including the proportion of variables harmonised by each cohort and the number of children for whom harmonised core data are available. EU Child Cohort Network data will be analysed using a federated analysis platform, removing the need to physically transfer data and thus making the data more accessible to researchers. The network will add value to participating cohorts by increasing statistical power and exposure heterogeneity, as well as facilitating cross-cohort comparisons, cross-validation and replication. Our aim is to motivate other cohorts to join the network and encourage the use of the EU Child Cohort Network by the wider research community.

The LifeCycle Project-EU Child Cohort Network: a federated analysis infrastructure and harmonized data of more than 250,000 children and parents.

Early life is an important window of opportunity to improve health across the full lifecycle. An accumulating body of evidence suggests that exposure to adverse stressors during early life leads to developmental adaptations, which subsequently affect disease risk in later life. Also, geographical, socio-economic, and ethnic differences are related to health inequalities from early life onwards. To address these important public health challenges, many European pregnancy and childhood cohorts have been established over the last 30 years. The enormous wealth of data of these cohorts has led to important new biological insights and important impact for health from early life onwards. The impact of these cohorts and their data could be further increased by combining data from different cohorts. Combining data will lead to the possibility of identifying smaller effect estimates, and the opportunity to better identify risk groups and risk factors leading to disease across the lifecycle across countries. Also, it enables research on better causal understanding and modelling of life course health trajectories. The EU Child Cohort Network, established by the Horizon2020-funded LifeCycle Project, brings together nineteen pregnancy and childhood cohorts, together including more than 250,000 children and their parents. A large set of variables has been harmonised and standardized across these cohorts. The harmonized data are kept within each institution and can be accessed by external researchers through a shared federated data analysis platform using the R-based platform DataSHIELD, which takes relevant national and international data regulations into account. The EU Child Cohort Network has an open character. All protocols for data harmonization and setting up the data analysis platform are available online. The EU Child Cohort Network creates great opportunities for researchers to use data from different cohorts, during and beyond the LifeCycle Project duration. It also provides a novel model for collaborative research in large research infrastructures with individual-level data. The LifeCycle Project will translate results from research using the EU Child Cohort Network into recommendations for targeted prevention strategies to improve health trajectories for current and future generations by optimizing their earliest phases of life.

Chondroma of the falx cerebri: A case report and review of literature.

Chondroma is a benign cartilage-forming tumor which usually occurs in small bones of extremities but occasionally occurs in the brain. Usually, intracranial chondromas originate from skull base; however, chondroma of the falx cerebri is a very rare condition. We here report a rare case of falcine chondroma in a 19-year-old man who had normal physical examination without signs of any syndromic disorder. The neuroimaging findings were inconclusive, and the diagnosis was based on histopathological examination. The purpose of this paper is to raise attention about intracranial chondromas and suggest that chondroma must be ruled out in any patient presenting with masses arising from the falx.

Motor performance in early life and participation in leisure-time physical activity up to age 68 years.

BACKGROUND: This study examined associations between motor performance in early life and leisure-time physical activity (LTPA) participation across adulthood, and whether these changed with age. METHODS: Data were from 2526 participants from the Medical Research Council National Survey of Health and Development. Motor indicators were mother-reported ages at first standing and walking, teacher-rated games ability at age 13, and finger- and foot-tapping speed at age 15. LTPA was reported at ages 36, 43, 53, 60-64, and 68 years and classed at each age as none, moderate (1-4/mo), or regular (≥5/mo). Associations were examined using mixed-effects Poisson regression models with robust error variance. RESULTS: Better ability at games and faster tapping speed were associated with more frequent participation in LTPA across adulthood, for example, fully adjusted relative risk of regular LTPA across adulthood (vs none) for above-average ability (vs below average or average) = 1.46 (95% CI 1.32, 1.61); and per 10-unit higher number of finger-taps/15 seconds = 1.04 (95% CI 1.02, 1.07). These associations did not vary by age (P ≥ .33 for interactions with age at LTPA). Ages at reaching motor milestones were not associated with LTPA (eg, fully adjusted relative risk of regular LTPA across adulthood for walking ≤10 and ≥18 months (vs 11-17 months) were 1.01 (95% CI 0.86, 1.20) and 0.89 (95% CI 0.75, 1.06) respectively. CONCLUSIONS: Better ability at games and faster tapping speed in adolescence were associated with greater participation in LTPA throughout adult life; from age 36 up to age 68. Childhood motor skill interventions may therefore have the potential to promote lifelong LTPA.

Correlates of high-impact physical activity measured objectively in older British adults.

Background: Exposure to higher magnitude vertical impacts is thought to benefit bone health. The correlates of this high-impact physical activity (PA) in later life are unknown. Methods: Participants were from the Cohort for Skeletal Health in Bristol and Avon, Hertfordshire Cohort Study and MRC National Survey of Health and Development. Associations of demographic, behavioural, physiological and psychological factors with vertical acceleration peaks ≥1.5 g (i.e. high-impact PA) from 7-day hip-worn accelerometer recordings were examined using linear regression. Results: A total of 1187 participants (mean age = 72.7 years, 66.6% females) were included. Age, sex, education, active transport, self-reported higher impact PA, walking speed and self-rated health were independently associated with high-impact PA whereas BMI and sleep quality showed borderline independent associations. For example, differences in log-high-impact counts were 0.50 (P < 0.001) for men versus women and -0.56 (P < 0.001) for worst versus best self-rated health. Our final model explained 23% of between-participant variance in high impacts. Other correlates were not associated with high-impact activity after adjustment. Conclusions: Besides age and sex, several factors were associated with higher impact PA in later life. Our findings help identify characteristics of older people that might benefit from interventions designed to promote osteogenic PA.

Childhood socioeconomic position and adult leisure-time physical activity: a systematic review.

Regular leisure-time physical activity (LTPA) benefits health and is thought to be less prevalent in lower socioeconomic groups. Evidence suggests that childhood socioeconomic circumstances can impact on adult health and behaviour however, it is unclear if this includes an influence on adult LTPA. This review tested the hypothesis that a lower childhood socioeconomic position (SEP) is associated with less frequent LTPA during adulthood. Studies were located through a systematic search of MEDLINE, Embase, PsycINFO, CINAHL and SPORTDiscus and by searching reference lists. Eligible studies were English-language publications testing the association between any indicator of childhood SEP and an LTPA outcome measured during adulthood. Forty-five papers from 36 studies, most of which were European, were included. In most samples, childhood SEP and LTPA were self-reported in midlife. Twenty-two studies found evidence to support the review's hypothesis and thirteen studies found no association. Accounting for own adult SEP partly attenuated associations. There was more evidence of an association in British compared with Scandinavian cohorts and in women compared with men. Results did not vary by childhood SEP indicator or age at assessment of LTPA. This review found evidence of an association between less advantaged childhood SEP and less frequent LTPA during adulthood. Understanding how associations vary by gender and place could provide insights into underlying pathways.

Parental infertility and offspring cardiometabolic trajectories: a pooled analysis of three European cohorts.

OBJECTIVE: To assess whether parental infertility is associated with differences in cardiometabolic trajectories in offspring. DESIGN: Pooled observational analysis in three prospective cohorts. SETTING: Three nationwide pregnancy cohorts. PATIENTS: A total of 14,609 singletons from the UK Avon Longitudinal Study of Parents and Children, the Portuguese Geraçao 21, and the Amsterdam Born Children and Their Development study. Each cohort contributed data up to ages 26, 12, and 13 years, respectively. INTERVENTION: Parental infertility is defined as time-to-pregnancy of ≥12 months (n = 1,392, 9.5%). MAIN OUTCOME MEASURES: Trajectories of body mass index (BMI), waist circumference, systolic blood pressure, diastolic blood pressure, low-density lipoprotein cholesterol (LDL-C) level, high-density lipoprotein cholesterol (HDL-C) level, triglycerides level, and glucose level were compared in the offspring of couples with and without infertility. Trajectories were modeled using mixed-effects models with natural cubic splines adjusting for cohort, sex of the offspring, and maternal factors (age, BMI, smoking, educational level, parity, and ethnicity). Predicted levels of cardiometabolic traits up to 25 years of age were compared with parental infertility. RESULTS: Offspring of couples with infertility had increasingly higher BMI (difference in mean predicted levels by age 25 years: 1.09 kg/m2, 95% confidence interval [0.68-1.50]) and suggestively higher diastolic blood pressure at age 25 years (1.21 mmHg [-0.003 to 2.43]). Their LDL-C tended to be higher, and their HDL-C values tended to be lower over time (age: 25 years, LDL-C: 4.07% [-0.79 to 8.93]; HDL-C: -2.78% [-6.99 to 1.43]). At age 17 years, offspring of couples with infertility had higher waist circumference (1.05 cm [0.11-1.99]) and systolic blood pressure (age: 17 years; 0.93 mmHg [0.044-1.81]), but these differences attenuated at later ages. No intergroup differences in triglyceride and glucose level trajectories were observed. Further adjustment for paternal age, BMI, smoking, and educational level, and both parents' histories of diabetes and hypertension in the cohort with this information available (Avon Longitudinal Study of Parents and Children) did not attenuate intergroup differences. CONCLUSION: Offspring of couples with infertility relative to those of fertile couples have increasingly higher BMI over the years, suggestively higher blood pressure levels, and tend to have greater values of LDL-C and lower values of HDL-C with age.

Prenatal Urban Environment and Blood Pressure Trajectories From Childhood to Early Adulthood.

Background: Prenatal urban environmental exposures have been associated with blood pressure in children. The dynamic of these associations across childhood and later ages is unknown. Objectives: The purpose of this study was to assess associations of prenatal urban environmental exposures with blood pressure trajectories from childhood to early adulthood. Methods: Repeated measures of systolic blood pressure (SBP) and diastolic blood pressure (DBP) were collected in up to 7,454 participants from a UK birth cohort. Prenatal urban exposures (n = 43) covered measures of noise, air pollution, built environment, natural spaces, traffic, meteorology, and food environment. An exposome-wide association study approach was used. Linear spline mixed-effects models were used to model associations of each exposure with trajectories of blood pressure. Replication was sought in 4 independent European cohorts (up to 9,261). Results: In discovery analyses, higher humidity was associated with a faster increase (mean yearly change in SBP for an interquartile range increase in humidity: 0.29 mm Hg/y, 95% CI: 0.20-0.39) and higher temperature with a slower increase (mean yearly change in SBP per interquartile range increase in temperature: -0.17 mm Hg/y, 95% CI: -0.28 to -0.07) in SBP in childhood. Higher levels of humidity and air pollution were associated with faster increase in DBP in childhood and slower increase in adolescence. There was little evidence of an association of other exposures with change in SBP or DBP. Results for humidity and temperature, but not for air pollution, were replicated in other cohorts. Conclusions: Replicated findings suggest that higher prenatal humidity and temperature could modulate blood pressure changes across childhood.

Green space exposure and blood DNA methylation at birth and in childhood - A multi-cohort study.

Green space exposure has been associated with improved mental, physical and general health. However, the underlying biological mechanisms remain largely unknown. The aim of this study was to investigate the association between green space exposure and cord and child blood DNA methylation. Data from eight European birth cohorts with a total of 2,988 newborns and 1,849 children were used. Two indicators of residential green space exposure were assessed: (i) surrounding greenness (satellite-based Normalized Difference Vegetation Index (NDVI) in buffers of 100 m and 300 m) and (ii) proximity to green space (having a green space ≥ 5,000 m2 within a distance of 300 m). For these indicators we assessed two exposure windows: (i) pregnancy, and (ii) the period from pregnancy to child blood DNA methylation assessment, named as cumulative exposure. DNA methylation was measured with the Illumina 450K or EPIC arrays. To identify differentially methylated positions (DMPs) we fitted robust linear regression models between pregnancy green space exposure and cord blood DNA methylation and between cumulative green space exposure and child blood DNA methylation. Two sensitivity analyses were conducted: (i) without adjusting for cellular composition, and (ii) adjusting for air pollution. Cohort results were combined through fixed-effect inverse variance weighted meta-analyses. Differentially methylated regions (DMRs) were identified from meta-analysed results using the Enmix-combp and DMRcate methods. There was no statistical evidence of pregnancy or cumulative exposures associating with any DMP (False Discovery Rate, FDR, p-value < 0.05). However, surrounding greenness exposure was inversely associated with four DMRs (three in cord blood and one in child blood) annotated to ADAMTS2, KCNQ1DN, SLC6A12 and SDK1 genes. Results did not change substantially in the sensitivity analyses. Overall, we found little evidence of the association between green space exposure and blood DNA methylation. Although we identified associations between surrounding greenness exposure with four DMRs, these findings require replication.

Genome-wide analyses identify 21 infertility loci and over 400 reproductive hormone loci across the allele frequency spectrum.

Genome-wide association studies (GWASs) may help inform treatments for infertility, whose causes remain unknown in many cases. Here we present GWAS meta-analyses across six cohorts for male and female infertility in up to 41,200 cases and 687,005 controls. We identified 21 genetic risk loci for infertility (P≤5E-08), of which 12 have not been reported for any reproductive condition. We found positive genetic correlations between endometriosis and all-cause female infertility (rg=0.585, P=8.98E-14), and between polycystic ovary syndrome and anovulatory infertility (rg=0.403, P=2.16E-03). The evolutionary persistence of female infertility-risk alleles in EBAG9 may be explained by recent directional selection. We additionally identified up to 269 genetic loci associated with follicle-stimulating hormone (FSH), luteinising hormone, oestradiol, and testosterone through sex-specific GWAS meta-analyses (N=6,095-246,862). While hormone-associated variants near FSHB and ARL14EP colocalised with signals for anovulatory infertility, we found no rg between female infertility and reproductive hormones (P>0.05). Exome sequencing analyses in the UK Biobank (N=197,340) revealed that women carrying testosterone-lowering rare variants in GPC2 were at higher risk of infertility (OR=2.63, P=1.25E-03). Taken together, our results suggest that while individual genes associated with hormone regulation may be relevant for fertility, there is limited genetic evidence for correlation between reproductive hormones and infertility at the population level. We provide the first comprehensive view of the genetic architecture of infertility across multiple diagnostic criteria in men and women, and characterise its relationship to other health conditions.