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Benefits of cooperation among large-scale cohort studies and human biomonitoring projects in environmental health research: An exercise in blood lead analysis of the Environment and Child Health International Birth Cohort Group.

ABSTRACT: A number of prospective cohort studies are ongoing worldwide to investigate the impact of foetal and neonatal exposures to chemical substances on child health. To assess multiple exposure (mixture) effects and low prevalence health outcomes it is useful to pool data from several studies and conduct mega-data-analysis. To discuss a path towards data harmonization, representatives from several large-scale birth cohort studies and a biomonitoring programme formed a collaborative group, the Environment and Child Health International Birth Cohort Group (ECHIBCG). In this study, an intra-laboratory trial was performed to harmonize existing blood lead measurements within the groups' studies. Then, decentralized analyses were conducted in individual countries' laboratories to evaluate blood lead levels (BLL) in each study. The measurements of pooled BLL samples in French, German and three Japanese laboratories resulted in an overall mean blood lead concentration of 8.66??g?l-1 (95% confidence interval: 8.59-8.72??g?l-1) with 3.0% relative standard deviation. Except for China's samples, BLL from each study were comparable with mean concentrations below or close to 10??g?l-1. The decentralized multivariate analyses revealed that all models had coefficients of determination below 0.1. Determinants of BLL were current smoking, age >35 years and overweight or obese status. The three variables were associated with an increase in BLL in each of the five studies, most strongly in France by almost 80% and the weakest effect being in Norway with only 15%; for Japan, with the far largest sample (~18,000), the difference was 36%. This study successfully demonstrated that the laboratory analytical methods were sufficiently similar to allow direct comparison of data and showed that it is possible to harmonize the epidemiological data for joint analysis. This exercise showed the challenges in decentralized data analyses and reinforces the need for data harmonization among studies.

SUBMITTER: Nakayama SF

PROVIDER: S-EPMC6732228 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Benefits of cooperation among large-scale cohort studies and human biomonitoring projects in environmental health research: An exercise in blood lead analysis of the Environment and Child Health International Birth Cohort Group.

Nakayama Shoji F SF Espina Carolina C Kamijima Michihiro M Magnus Per P Charles Marie-Aline MA Zhang Jun J Wolz Birgit B Conrad André A Murawski Aline A Iwai-Shimada Miyuki M Zaros Cécile C Caspersen Ida Henriette IH Kolossa-Gehring Marike M Meltzer Helle Margrete HM Olsen Sjurdur F SF Etzel Ruth A RA Schüz Joachim J

International journal of hygiene and environmental health 20190718 8

A number of prospective cohort studies are ongoing worldwide to investigate the impact of foetal and neonatal exposures to chemical substances on child health. To assess multiple exposure (mixture) effects and low prevalence health outcomes it is useful to pool data from several studies and conduct mega-data-analysis. To discuss a path towards data harmonization, representatives from several large-scale birth cohort studies and a biomonitoring programme formed a collaborative group, the Environm ...[more]

PMID: 31327570

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Project description:BackgroundAdverse childhood experiences (ACEs) are negatively associated with a range of child health outcomes. In this study, we explored associations between five individual ACEs and child mental health diagnoses or symptoms. ACEs included living with someone who had an alcohol-related problem, common mental health disorder or serious mental illness, or experienced victimisation or death of a household member.MethodsWe analysed data from a population-level electronic cohort of children in Wales, UK, (N = 191,035) between the years of 1998 and 2012. We used Cox regression with discrete time-varying exposure variables to model time to child mental health diagnosis during the first 15 years of life. Child mental health diagnoses include five categories: (i) externalising symptoms (anti-social behaviour), (ii) internalising symptoms (stress, anxiety, depression), (iii) developmental delay (e.g. learning disability), (iv) other (e.g. eating disorder, personality disorders), and (v) any mental health diagnosis, which was created by combining externalising symptoms, internalising symptoms and other. Our analyses were adjusted for social deprivation and perinatal risk factors.ResultsThere were strong univariable associations between the five individual ACEs, sociodemographic and perinatal factors (e.g. gestational weight at birth) and an increased risk of child mental health diagnoses. After adjusting for sociodemographic and perinatal aspects, there was a remaining conditional increased risk of any child mental health diagnosis, associated with victimisation (conditional hazard ratio (cHR) 1.90, CI 95% 1.34-2.69), and living with an adult with a common mental health diagnosis (cHR 1.63, CI 95% 1.52-1.75). Coefficients of product terms between ACEs and deprivation were not statistically significant.ConclusionThe increased risk of child mental health diagnosis associated with victimisation, or exposure to common mental health diagnoses, and alcohol problems in the household supports the need for policy measures and intervention strategies for children and their families.

Project description:ObjectiveThis study investigates the associations between maternal health and health-related behaviours (nutrition, physical activity, alcohol consumption and smoking) both during pregnancy and up to 15 months from childbirth and children's health outcomes during infancy and adolescence (general health, presence of a chronic illness, and physical health outcome index).MethodsThis study used Wave 1 (2004) and Wave 7 (2016) data from the Longitudinal Survey of Australian Children (LSAC). We measured mothers' general health, presence of a medical condition during pregnancy and mental health during pregnancy or in the year after childbirth. We subsequently measured the children's general health, presence of a medical condition, and physical health outcome index at ages 0-1 (infancy) and 12-13 (adolescence). Binary logistic and linear regression analyses were performed to examine the association between the mothers' health-related variables and their children's health.ResultsOur results showed that poor general health of the mother in the year after childbirth was associated with higher odds of poor health in infants and adolescents in all three dimensions: poor general health (OR: 3.13, 95% CI: 2.16-4.52 for infants; OR: 1.39, 95% CI: 0.95-2.04 for adolescents), presence of a chronic condition (OR: 1.47, 95% CI: 1.19-1.81 for adolescents) and lower physical health score (b = -0.94, p-value <0.05 for adolescents). Our study also revealed that the presence of a chronic condition in mothers during pregnancy significantly increased the likelihood of the presence of a chronic condition in their offspring during infancy (OR: 1.31, 95% CI: 1.12-1.54) and during adolescence (OR: 1.45, 95% CI: 1.20-1.75). The study found that stressful life events faced by mothers increase the odds of poor general health or any chronic illness during adolescence, while stress, anxiety or depression during pregnancy and psychological distress in the year after childbirth increase the odds of any chronic illness during infancy.ConclusionsThe present study found evidence that poor maternal physical and mental health during pregnancy or up to 15 months from childbirth has adverse health consequences for their offspring as measured by general health, presence of chronic health conditions, and physical health index scores. This suggests that initiatives to improve maternal physical and mental health would not only improve child health but would also reduce the national health burden.

Project description:All subjects were recruited at Centennial Women?s Hospital and the Perinatal Research Center in Nashville, TN beginning in 2003. Pregnant women were enrolled during their first clinical visit after obtaining informed consent as described previously. Demographic and clinical data specific to the fetus was collected from clinical records. Gestational age of the neonate was determined by maternal reporting of the last menstrual period and corroboration by ultrasound dating. Accurate knowledge of gestational age (GA) is essential for proper monitoring and care of neonates. However, accurate GA measures are often not available. DNA methylation has previously been shown to associate with GA, and has been used to accurately predict chronological age in adults. In the current study, we examine whether DNA methylation in cord blood can be used to predict gestational age at birth. Results: We found that GA can be accurately predicted from DNA methylation of neonatal cord blood and blood spot samples (DNAm GA), using 148 CpG sites selected through elastic net regression in six training datasets (N=207). We evaluated predictive accuracy in six testing datasets (N=1,202), and found that the accuracy of DNAm GA meets or exceeds accuracy of gestational age estimates based on established methods. We also found an increased DNAm GA, relative to clinical GA, was associated with increased birthweight percentile (p=.00057), adjusting for GA, sex, and ancestry, suggesting that DNAm GA could represent developmental age more accurately than clinical estimates of GA. Conclusions: Further development of this predictor could provide a method of accurate neonatal estimation of GA for use in resource-limited populations, or in cases where GA cannot be estimated clinically. When clinical estimates are available, the predictor can be used to test hypotheses related to developmental age and other early life circumstances, and may provide increased accuracy beyond clinical estimates.

Dataset Information

Benefits of cooperation among large-scale cohort studies and human biomonitoring projects in environmental health research: An exercise in blood lead analysis of the Environment and Child Health International Birth Cohort Group.

Publications

Benefits of cooperation among large-scale cohort studies and human biomonitoring projects in environmental health research: An exercise in blood lead analysis of the Environment and Child Health International Birth Cohort Group.

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