33 research outputs found

    Prenatal Stress Exposure Related to Maternal Bereavement and Risk of Childhood Overweight

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    BACKGROUND: It has been suggested that prenatal stress contributes to the risk of obesity later in life. In a population-based cohort study, we examined whether prenatal stress related to maternal bereavement during pregnancy was associated with the risk of overweight in offspring during school age. METHODOLOGY/PRINCIPAL FINDINGS: We followed 65,212 children born in Denmark from 1970-1989 who underwent health examinations from 7 to 13 years of age in public or private schools in Copenhagen. We identified 459 children as exposed to prenatal stress, defined by being born to mothers who were bereaved by death of a close family member from one year before pregnancy until birth of the child. We compared the prevalence of overweight between the exposed and the unexposed. Body mass index (BMI) values and prevalence of overweight were higher in the exposed children, but not significantly so until from 10 years of age and onwards, as compared with the unexposed children. For example, the adjusted odds ratio (OR) for overweight was 1.68 (95% confidence interval [CI] 1.08-2.61) at 12 years of age and 1.63 (95% CI 1.00-2.61) at 13 years of age. The highest ORs were observed when the death occurred in the period from 6 to 0 month before pregnancy (OR 3.31, 95% CI 1.71-6.42 at age 12, and OR 2.31, 95% CI 1.08-4.97 at age 13). CONCLUSIONS/SIGNIFICANCE: Our results suggest that severe pre-pregnancy stress is associated with an increased risk of overweight in the offspring in later childhood

    A proposed framework for the systematic review and integrated assessment (SYRINA) of endocrine disrupting chemicals

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    Background - The issue of endocrine disrupting chemicals (EDCs) is receiving wide attention from both the scientific and regulatory communities. Recent analyses of the EDC literature have been criticized for failing to use transparent and objective approaches to draw conclusions about the strength of evidence linking EDC exposures to adverse health or environmental outcomes. Systematic review methodologies are ideal for addressing this issue as they provide transparent and consistent approaches to study selection and evaluation. Objective methods are needed for integrating the multiple streams of evidence (epidemiology, wildlife, laboratory animal, in vitro, and in silico data) that are relevant in assessing EDCs. Methods - We have developed a framework for the systematic review and integrated assessment (SYRINA) of EDC studies. The framework was designed for use with the International Program on Chemical Safety (IPCS) and World Health Organization (WHO) definition of an EDC, which requires appraisal of evidence regarding 1) association between exposure and an adverse effect, 2) association between exposure and endocrine disrupting activity, and 3) a plausible link between the adverse effect and the endocrine disrupting activity. Results - Building from existing methodologies for evaluating and synthesizing evidence, the SYRINA framework includes seven steps: 1) Formulate the problem; 2) Develop the review protocol; 3) Identify relevant evidence; 4) Evaluate evidence from individual studies; 5) Summarize and evaluate each stream of evidence; 6) Integrate evidence across all streams; 7) Draw conclusions, make recommendations, and evaluate uncertainties. The proposed method is tailored to the IPCS/WHO definition of an EDC but offers flexibility for use in the context of other definitions of EDCs. Conclusions - When using the SYRINA framework, the overall objective is to provide the evidence base needed to support decision making, including any action to avoid/minimise potential adverse effects of exposures. This framework allows for the evaluation and synthesis of evidence from multiple evidence streams. Finally, a decision regarding regulatory action is not only dependent on the strength of evidence, but also the consequences of action/inaction, e.g. limited or weak evidence may be sufficient to justify action if consequences are serious or irreversible.The workshops that supported the writing of this manuscript were funded by the Swedish Foundation for Strategic Environmental Research “Mistra”. LNV was funded by Award Number K22ES025811 from the National Institute of Environmental Health Sciences of the National Institutes of Health. TJW was funded by The Clarence Heller Foundation (A123547), the Passport Foundation, the Forsythia Foundation, the National Institute of Environmental Health Sciences (grants ES018135 and ESO22841), and U.S. EPA STAR grants (RD83467801 and RD83543301). JT was funded by the Academy of Finland and Sigrid Juselius. UH was funded by the Danish EPA. KAK was funded by the Canada Research Chairs program grant number 950–230607

    Concentration addition, independent action and generalized concentration addition models for mixture effect prediction of sex hormone synthesis in vitro

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    Humans are concomitantly exposed to numerous chemicals. An infinite number of combinations and doses thereof can be imagined. For toxicological risk assessment the mathematical prediction of mixture effects, using knowledge on single chemicals, is therefore desirable. We investigated pros and cons of the concentration addition (CA), independent action (IA) and generalized concentration addition (GCA) models. First we measured effects of single chemicals and mixtures thereof on steroid synthesis in H295R cells. Then single chemical data were applied to the models; predictions of mixture effects were calculated and compared to the experimental mixture data. Mixture 1 contained environmental chemicals adjusted in ratio according to human exposure levels. Mixture 2 was a potency adjusted mixture containing five pesticides. Prediction of testosterone effects coincided with the experimental Mixture 1 data. In contrast, antagonism was observed for effects of Mixture 2 on this hormone. The mixtures contained chemicals exerting only limited maximal effects. This hampered prediction by the CA and IA models, whereas the GCA model could be used to predict a full dose response curve. Regarding effects on progesterone and estradiol, some chemicals were having stimulatory effects whereas others had inhibitory effects. The three models were not applicable in this situation and no predictions could be performed. Finally, the expected contributions of single chemicals to the mixture effects were calculated. Prochloraz was the predominant but not sole driver of the mixtures, suggesting that one chemical alone was not responsible for the mixture effects. In conclusion, the GCA model seemed to be superior to the CA and IA models for the prediction of testosterone effects. A situation with chemicals exerting opposing effects, for which the models could not be applied, was identified. In addition, the data indicate that in non-potency adjusted mixtures the effects cannot always be accounted for by single chemicals

    Numerical Study of Conjugate Natural Convection from Discrete Heat Sources.

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    noThe coupling between natural convection and conduction within rectangular enclosure was investigated numerically. Three separate heat sources were flush mounted on a vertical wall and an isoflux condition was applied at the back of heat sources. The governing equations were solved using control volume formulation. A modified Rayleigh number and a substrate/fluid thermal conductivity ratio were used in the range 10^4 −10^7 and 10−10^3 respectively. The investigation was extended to examine high thermal conductivity ratio values. The results illustrated that, when Rayleigh number increased the dimensionless heat flux and local Nusselt number increased and the boundary layers along hot, cold and horizontal walls were reduced significantly. An opposite behaviour for the thermal spreading in the substrate and the dimensionless temperature, were decreased for higher Rayleigh number. Moreover, the thermal spreading in the substrate increased for higher substrate conductivity, which affected the temperature level. However the effect of the substrate is negligible when the thermal conductivity ratio higher than 1,500.The full text of book chapters are not available for self deposit under the Publisher's copyright restrictions
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